2024
Villa, Manny; Casilari, Eduardo
Wearable Fall Detectors Based on Low Power Transmission Systems: A Systematic Review Journal Article
In: Technologies, vol. 12, no. 9, 2024, ISSN: 2227-7080.
@article{technologies12090166,
title = {Wearable Fall Detectors Based on Low Power Transmission
Systems: A Systematic Review},
author = {Manny Villa and Eduardo Casilari},
url = {https://www.mdpi.com/2227-7080/12/9/166},
doi = {10.3390/technologies12090166},
issn = {2227-7080},
year = {2024},
date = {2024-01-01},
journal = {Technologies},
volume = {12},
number = {9},
abstract = {Early attention to individuals who suffer falls is a critical aspect when determining the consequences of such accidents, which are among the leading causes of mortality and disability in older adults. For this reason and considering the high number of older adults living alone, the development of automatic fall alerting systems has garnered significant research attention over the past decade. A key element for deploying a fall detection system (FDS) based on wearables is the wireless transmission method employed to transmit the medical alarms. In this regard, the vast majority of prototypes in the related literature utilize short-range technologies, such as Bluetooth, which must be complemented by the existence of a gateway device (e.g., a smartphone). In other studies, standards like Wi-Fi or 3G communications are proposed, which offer greater range but come with high power consumption, which can be unsuitable for most wearables, and higher service fees. In addition, they require reliable radio coverage, which is not always guaranteed in all application scenarios. An interesting alternative to these standards is Low Power Wide Area Network (LPWAN) technologies, which minimize both energy consumption and hardware costs while maximizing transmission range. This article provides a comprehensive search and review of that works in the literature that have implemented and evaluated wearable FDSs utilizing LPWAN interfaces to transmit alarms. The review systematically examines these proposals, considering various operational aspects and identifying key areas that have not yet been adequately addressed for the viable implementation of such detectors.},
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Early attention to individuals who suffer falls is a critical aspect when determining the consequences of such accidents, which are among the leading causes of mortality and disability in older adults. For this reason and considering the high number of older adults living alone, the development of automatic fall alerting systems has garnered significant research attention over the past decade. A key element for deploying a fall detection system (FDS) based on wearables is the wireless transmission method employed to transmit the medical alarms. In this regard, the vast majority of prototypes in the related literature utilize short-range technologies, such as Bluetooth, which must be complemented by the existence of a gateway device (e.g., a smartphone). In other studies, standards like Wi-Fi or 3G communications are proposed, which offer greater range but come with high power consumption, which can be unsuitable for most wearables, and higher service fees. In addition, they require reliable radio coverage, which is not always guaranteed in all application scenarios. An interesting alternative to these standards is Low Power Wide Area Network (LPWAN) technologies, which minimize both energy consumption and hardware costs while maximizing transmission range. This article provides a comprehensive search and review of that works in the literature that have implemented and evaluated wearable FDSs utilizing LPWAN interfaces to transmit alarms. The review systematically examines these proposals, considering various operational aspects and identifying key areas that have not yet been adequately addressed for the viable implementation of such detectors.
Casilari, Eduardo; Barbosa-Galeano, Jennifer; González-Cañete, Francisco J.
UMAHand: A dataset of inertial signals of typical hand activities Journal Article
In: Data in Brief, vol. 55, pp. 110731, 2024, ISSN: 2352-3409.
@article{CASILARI2024110731,
title = {UMAHand: A dataset of inertial signals of typical hand activities},
author = {Eduardo Casilari and Jennifer Barbosa-Galeano and Francisco J. González-Cañete},
url = {https://www.sciencedirect.com/science/article/pii/S235234092400698X},
doi = {https://doi.org/10.1016/j.dib.2024.110731},
issn = {2352-3409},
year = {2024},
date = {2024-01-01},
journal = {Data in Brief},
volume = {55},
pages = {110731},
abstract = {Given the popularity of wrist-worn devices, particularly smartwatches, the identification of manual movement patterns has become of utmost interest within the research field of Human Activity Recognition (HAR) systems. In this context, by leveraging the numerous sensors natively embedded in smartwatches, the HAR functionalities that can be implemented in a watch via software and in a very cost-efficient way cover a wide variety of applications, ranging from fitness trackers to gesture detectors aimed at disabled individuals (e.g., for sending alarms), promoting behavioral activation or healthy lifestyle habits. In this regard, for the development of artificial intelligence algorithms capable of effectively discriminating these activities, it is of great importance to have repositories of movements that allow the scientific community to train, evaluate, and benchmark new proposals of movement detectors. The UMAHand dataset offers a collection of files containing the signals captured by a Shimmer 3 sensor node, which includes an accelerometer, a gyroscope, a magnetometer and a barometer, during the execution of different typical hand movements. For that purpose, the measurements from these four sensors, gathered at a sampling rate of 100 Hz, were taken from a group of 25 volunteers (16 females and 9 males), aged between 18 and 56, during the performance of 29 daily life activities involving hand mobility. Participants wore the sensor node on their dominant hand throughout the experiments.},
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Given the popularity of wrist-worn devices, particularly smartwatches, the identification of manual movement patterns has become of utmost interest within the research field of Human Activity Recognition (HAR) systems. In this context, by leveraging the numerous sensors natively embedded in smartwatches, the HAR functionalities that can be implemented in a watch via software and in a very cost-efficient way cover a wide variety of applications, ranging from fitness trackers to gesture detectors aimed at disabled individuals (e.g., for sending alarms), promoting behavioral activation or healthy lifestyle habits. In this regard, for the development of artificial intelligence algorithms capable of effectively discriminating these activities, it is of great importance to have repositories of movements that allow the scientific community to train, evaluate, and benchmark new proposals of movement detectors. The UMAHand dataset offers a collection of files containing the signals captured by a Shimmer 3 sensor node, which includes an accelerometer, a gyroscope, a magnetometer and a barometer, during the execution of different typical hand movements. For that purpose, the measurements from these four sensors, gathered at a sampling rate of 100 Hz, were taken from a group of 25 volunteers (16 females and 9 males), aged between 18 and 56, during the performance of 29 daily life activities involving hand mobility. Participants wore the sensor node on their dominant hand throughout the experiments.
Silva, Carlos A.; Casilari, Eduardo; García-Bermúdez, Rodolfo
In: Data in Brief, vol. 55, pp. 110621, 2024, ISSN: 2352-3409.
@article{SILVA2024110621,
title = {UMATUG: A dataset of inertial signals of older and young adults using a gerontologic simulator collected during instrumented Timed Up and Go (iTUG) tests},
author = {Carlos A. Silva and Eduardo Casilari and Rodolfo García-Bermúdez},
url = {https://www.sciencedirect.com/science/article/pii/S2352340924005882},
doi = {https://doi.org/10.1016/j.dib.2024.110621},
issn = {2352-3409},
year = {2024},
date = {2024-01-01},
journal = {Data in Brief},
volume = {55},
pages = {110621},
abstract = {Timed Up and Go (TUG) test is one of the most popular clinical tools aimed at the assessment of functional mobility and fall risk in older adults. The automation of the analysis of TUG movements is of great medical interest not only to speed up the test but also to maximize the information inferred from the subjects under study. In this context, this article describes a dataset collected from a cohort of 69 experimental subjects (including 30 adults over 60 years), during the execution of several repetitions of the TUG test. In particular, the dataset includes the measurements gathered with four wearables devices embedding four sensors (accelerometer, gyroscope magnetometer and
barometer) located on four body locations (waist, wrist, ankle and chest). As a particularity, the dataset also includes the same measurements recorded when the young subjects repeat the test while wearing a commercial geriatric simulator, consisting of a set of weighted vests and other elements intended to replicate the limitations caused by aging. Thus, the generated dataset also enables the investigation into the potential of such tools to emulate the actual dynamics of older individuals.},
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Timed Up and Go (TUG) test is one of the most popular clinical tools aimed at the assessment of functional mobility and fall risk in older adults. The automation of the analysis of TUG movements is of great medical interest not only to speed up the test but also to maximize the information inferred from the subjects under study. In this context, this article describes a dataset collected from a cohort of 69 experimental subjects (including 30 adults over 60 years), during the execution of several repetitions of the TUG test. In particular, the dataset includes the measurements gathered with four wearables devices embedding four sensors (accelerometer, gyroscope magnetometer and
barometer) located on four body locations (waist, wrist, ankle and chest). As a particularity, the dataset also includes the same measurements recorded when the young subjects repeat the test while wearing a commercial geriatric simulator, consisting of a set of weighted vests and other elements intended to replicate the limitations caused by aging. Thus, the generated dataset also enables the investigation into the potential of such tools to emulate the actual dynamics of older individuals.
barometer) located on four body locations (waist, wrist, ankle and chest). As a particularity, the dataset also includes the same measurements recorded when the young subjects repeat the test while wearing a commercial geriatric simulator, consisting of a set of weighted vests and other elements intended to replicate the limitations caused by aging. Thus, the generated dataset also enables the investigation into the potential of such tools to emulate the actual dynamics of older individuals.
Silva, Carlos A.; Casilari, Eduardo; García-Bermúdez, Rodolfo
Cross-dataset evaluation of wearable fall detection systems using data from real falls and long-term monitoring of daily life Journal Article
In: Measurement, vol. 235, pp. 114992, 2024, ISSN: 0263-2241.
@article{SILVA2024114992,
title = {Cross-dataset evaluation of wearable fall detection systems using data from real falls and long-term monitoring of daily life},
author = {Carlos A. Silva and Eduardo Casilari and Rodolfo García-Bermúdez},
url = {https://www.sciencedirect.com/science/article/pii/S0263224124008777},
doi = {https://doi.org/10.1016/j.measurement.2024.114992},
issn = {0263-2241},
year = {2024},
date = {2024-01-01},
journal = {Measurement},
volume = {235},
pages = {114992},
abstract = {The evaluation of fall detection systems based on wearables is controversial as most studies in the literature benchmark their proposals against falls that are simulated by experimental subjects under unrealistic laboratory conditions. In order to systematically investigate the suitability of this procedure, this paper evaluates a wide set of artificial intelligence algorithms used for fall detection, when trained with a large number of datasets containing acceleration samples captured during the emulation of falls and ordinary movements and then tested with the signals of both actual falls and long-term traces collected from the constant monitoring of users during their daily routines. The results, based on a large number of repositories, show a remarkable degradation in all performance metrics (sensitivity, specificity and false alarm hourly rate) with respect to the typical case in which the detectors are tested with the same types of laboratory movements for which they were trained.},
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The evaluation of fall detection systems based on wearables is controversial as most studies in the literature benchmark their proposals against falls that are simulated by experimental subjects under unrealistic laboratory conditions. In order to systematically investigate the suitability of this procedure, this paper evaluates a wide set of artificial intelligence algorithms used for fall detection, when trained with a large number of datasets containing acceleration samples captured during the emulation of falls and ordinary movements and then tested with the signals of both actual falls and long-term traces collected from the constant monitoring of users during their daily routines. The results, based on a large number of repositories, show a remarkable degradation in all performance metrics (sensitivity, specificity and false alarm hourly rate) with respect to the typical case in which the detectors are tested with the same types of laboratory movements for which they were trained.
Casilari, Eduardo; Gonzalez-Cañete, Francisco Javier
A Smartwatch-based Approach for Oral Health Monitoring using Deep Learning Proceedings Article
In: Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments, pp. 343–350, Association for Computing Machinery, Crete, Greece, 2024, ISBN: 9798400717604.
@inproceedings{10.1145/3652037.3663912,
title = {A Smartwatch-based Approach for Oral Health Monitoring using Deep Learning},
author = {Eduardo Casilari and Francisco Javier Gonzalez-Cañete},
url = {https://doi.org/10.1145/3652037.3663912},
doi = {10.1145/3652037.3663912},
isbn = {9798400717604},
year = {2024},
date = {2024-01-01},
booktitle = {Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments},
pages = {343–350},
publisher = {Association for Computing Machinery},
address = {Crete, Greece},
series = {PETRA '24},
abstract = {Monitoring toothbrushing is of great importance to promote the improvement of oral health habits. In this study wearable devices and artificial intelligence methods are combined to identify tooth brushing. The focus is on utilizing convolutional neural networks to recognize brushing gestures based on short samples of accelerometer data collected from wrist-worn devices. As a benchmarking dataset, we train and test the model with a public database containing signals obtained from a wide set of experimental subjects performing a variety of different manual actions. The results show the high effectiveness of the detector, which achieves quality metrics (sensitivity and specificity) higher than 95% when it is employed to discriminate brushing actions from other 23 hand movements. This performance is improved if the architecture is refined through a simple low-pass filtering of the classifier's decisions, aimed at correcting the classification of anomalous and isolated mobility patterns.},
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Monitoring toothbrushing is of great importance to promote the improvement of oral health habits. In this study wearable devices and artificial intelligence methods are combined to identify tooth brushing. The focus is on utilizing convolutional neural networks to recognize brushing gestures based on short samples of accelerometer data collected from wrist-worn devices. As a benchmarking dataset, we train and test the model with a public database containing signals obtained from a wide set of experimental subjects performing a variety of different manual actions. The results show the high effectiveness of the detector, which achieves quality metrics (sensitivity and specificity) higher than 95% when it is employed to discriminate brushing actions from other 23 hand movements. This performance is improved if the architecture is refined through a simple low-pass filtering of the classifier’s decisions, aimed at correcting the classification of anomalous and isolated mobility patterns.
2022
Santoyo-Ramón, Jose Antonio; Casilari, Eduardo; Cano-Garc’ıa, Jose Manuel
A Cross-Dataset Evaluation of Wearable Fall Detection Systems Proceedings Article
In: Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments, pp. 1–6, Association for Computing Machinery, Corfu, Greece, 2022, ISBN: 9781450396318.
@inproceedings{10.1145/3529190.3529191,
title = {A Cross-Dataset Evaluation of Wearable Fall Detection Systems},
author = {Jose Antonio Santoyo-Ramón and Eduardo Casilari and Jose Manuel Cano-Garc'ıa},
url = {https://doi.org/10.1145/3529190.3529191},
doi = {10.1145/3529190.3529191},
isbn = {9781450396318},
year = {2022},
date = {2022-01-01},
booktitle = {Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments},
pages = {1–6},
publisher = {Association for Computing Machinery},
address = {Corfu, Greece},
series = {PETRA '22},
abstract = {The popularity of wearables and their seamless integration into our daily lives have transformed these devices into an appealing resource to deploy automatic fall detection systems. During last years, a massive literature on new methods and algorithms for these wearable detectors has been produced. However, in most cases these algorithms are tested against one single (or at best two) datasets containing signals captured from falls and conventional movements. This work evaluates the behavior of a fall detection system based on a convolutional neural network when different public repositories of movements are alternatively used for training and testing the model. After a systematic cross-dataset evaluation involving four well-known datasets, we show the difficulty of extrapolating the results achieved by a certain classifier for a particular database when another dataset is considered. Results seem to indicate that classification methods tend to overlearn the particular conditions (typology of movements, characteristics of the employed sensor, experimental subjects) under which the training samples were generated.},
keywords = {},
pubstate = {published},
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}
The popularity of wearables and their seamless integration into our daily lives have transformed these devices into an appealing resource to deploy automatic fall detection systems. During last years, a massive literature on new methods and algorithms for these wearable detectors has been produced. However, in most cases these algorithms are tested against one single (or at best two) datasets containing signals captured from falls and conventional movements. This work evaluates the behavior of a fall detection system based on a convolutional neural network when different public repositories of movements are alternatively used for training and testing the model. After a systematic cross-dataset evaluation involving four well-known datasets, we show the difficulty of extrapolating the results achieved by a certain classifier for a particular database when another dataset is considered. Results seem to indicate that classification methods tend to overlearn the particular conditions (typology of movements, characteristics of the employed sensor, experimental subjects) under which the training samples were generated.
Castillo-Sánchez, José-Borja; Casilari, Eduardo; Cano-García, Jose Manuel; González-Parada, Eva; González-Cañete, Francisco J.
A Low-cost Home Monitoring Architecture for Human Activity Recognition Using Smartwatches Proceedings Article
In: 2022 IEEE International Mediterranean Conference on Communications and Networking (MeditCom), pp. 172-177, 2022.
@inproceedings{9928697,
title = {A Low-cost Home Monitoring Architecture for Human Activity Recognition Using Smartwatches},
author = {José-Borja Castillo-Sánchez and Eduardo Casilari and Jose Manuel Cano-García and Eva González-Parada and Francisco J. González-Cañete},
doi = {10.1109/MeditCom55741.2022.9928697},
year = {2022},
date = {2022-01-01},
booktitle = {2022 IEEE International Mediterranean Conference on Communications and Networking (MeditCom)},
pages = {172-177},
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Santoyo-Ramón, José Antonio; Casilari, Eduardo; Cano-García, José Manuel
A study of the influence of the sensor sampling frequency on the performance of wearable fall detectors Journal Article
In: Measurement, vol. 193, pp. 110945, 2022, ISSN: 0263-2241.
@article{ANTONIOSANTOYORAMON2022110945,
title = {A study of the influence of the sensor sampling frequency on the performance of wearable fall detectors},
author = {José Antonio Santoyo-Ramón and Eduardo Casilari and José Manuel Cano-García},
url = {https://www.sciencedirect.com/science/article/pii/S0263224122002226},
doi = {https://doi.org/10.1016/j.measurement.2022.110945},
issn = {0263-2241},
year = {2022},
date = {2022-01-01},
journal = {Measurement},
volume = {193},
pages = {110945},
abstract = {Last decade has witnessed a major research interest on wearable fall detection systems. Sampling rate in these detectors strongly affects the power consumption and required complexity of the employed wearables. This study investigates the effect of the sampling frequency on the efficacy of the detection process. For this purpose, we train a convolutional neural network to directly discriminate falls from conventional activities based on the raw acceleration signals captured by a transportable sensor. Then, we analyze the changes in the performance of this classifier when the sampling rate is progressively reduced. In contrast with previous studies, the detector is tested against a wide set of public repositories of benchmarking traces. The quality metrics achieved for the different frequencies and the analysis of the spectrum of the signals reveal that a sampling rate of 20 Hz can be enough to maximize the effectiveness of a fall detector.},
keywords = {},
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Last decade has witnessed a major research interest on wearable fall detection systems. Sampling rate in these detectors strongly affects the power consumption and required complexity of the employed wearables. This study investigates the effect of the sampling frequency on the efficacy of the detection process. For this purpose, we train a convolutional neural network to directly discriminate falls from conventional activities based on the raw acceleration signals captured by a transportable sensor. Then, we analyze the changes in the performance of this classifier when the sampling rate is progressively reduced. In contrast with previous studies, the detector is tested against a wide set of public repositories of benchmarking traces. The quality metrics achieved for the different frequencies and the analysis of the spectrum of the signals reveal that a sampling rate of 20 Hz can be enough to maximize the effectiveness of a fall detector.
Casilari, Eduardo; Silva, Carlos A.
An analytical comparison of datasets of Real-World and simulated falls intended for the evaluation of wearable fall alerting systems Journal Article
In: Measurement, vol. 202, pp. 111843, 2022, ISSN: 0263-2241.
@article{CASILARI2022111843,
title = {An analytical comparison of datasets of Real-World and simulated falls intended for the evaluation of wearable fall alerting systems},
author = {Eduardo Casilari and Carlos A. Silva},
url = {https://www.sciencedirect.com/science/article/pii/S0263224122010429},
doi = {https://doi.org/10.1016/j.measurement.2022.111843},
issn = {0263-2241},
year = {2022},
date = {2022-01-01},
journal = {Measurement},
volume = {202},
pages = {111843},
abstract = {Automatic fall detection is one of the most promising applications of wearables in the field of mobile health. The characterization of the effectiveness of wearable fall detectors is hampered by the inherent difficulty of testing these devices with real-world falls. In fact, practically all the proposals in the literature assess the detection algorithms with ‘scripted’ falls that are simulated in a controlled laboratory environment by a group of volunteers (normally young and healthy participants). Aiming at appraising the adequacy of this method, this work systematically compares the statistical characteristics of the acceleration signals from two databases with real falls and those computed from the simulated falls provided by 18 well-known repositories commonly employed by the related works. The results show noteworthy differences between the dynamics of emulated and real-life falls, which undermines the testing procedures followed to date and forces to rethink the strategies for evaluating wearable fall detectors.},
keywords = {},
pubstate = {published},
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Automatic fall detection is one of the most promising applications of wearables in the field of mobile health. The characterization of the effectiveness of wearable fall detectors is hampered by the inherent difficulty of testing these devices with real-world falls. In fact, practically all the proposals in the literature assess the detection algorithms with ‘scripted’ falls that are simulated in a controlled laboratory environment by a group of volunteers (normally young and healthy participants). Aiming at appraising the adequacy of this method, this work systematically compares the statistical characteristics of the acceleration signals from two databases with real falls and those computed from the simulated falls provided by 18 well-known repositories commonly employed by the related works. The results show noteworthy differences between the dynamics of emulated and real-life falls, which undermines the testing procedures followed to date and forces to rethink the strategies for evaluating wearable fall detectors.
2021
Santoyo-Ramón, José Antonio; Casilari, Eduardo; Cano-García, José Manuel
A study on the impact of the users’ characteristics on the performance of wearable fall detection system Journal Article
In: Scientific Reports, vol. 11, no. 23011, 2021, ISSN: 2045-2322.
@article{Ast/2021,
title = {A study on the impact of the users' characteristics on the performance of wearable fall detection system},
author = {José Antonio Santoyo-Ramón and Eduardo Casilari and José Manuel Cano-García},
url = {https://rdcu.be/cB5NF},
doi = {10.1038/s41598-021-02537-z},
issn = {2045-2322},
year = {2021},
date = {2021-11-01},
journal = {Scientific Reports},
volume = {11},
number = {23011},
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Santoyo-Ramón, Jose Antonio; Casilari, Eduardo; Cano-García, José Manuel
A Study of One-Class Classification Algorithms for Wearable Fall Sensors Journal Article
In: Biosensors, vol. 11, no. 8, pp. 284, 2021, ISSN: 2079-6374.
@article{Jos/ASt/2021,
title = {A Study of One-Class Classification Algorithms for Wearable Fall Sensors},
author = {Jose Antonio Santoyo-Ramón and Eduardo Casilari and José Manuel Cano-García},
url = {https://www.mdpi.com/2079-6374/11/8/284},
doi = {10.3390/bios11080284},
issn = {2079-6374},
year = {2021},
date = {2021-08-01},
journal = {Biosensors},
volume = {11},
number = {8},
pages = {284},
abstract = {In recent years, the popularity of wearable devices has fostered the investigation of automatic fall detection systems based on the analysis of the signals captured by transportable inertial sensors. Due to the complexity and variety of human movements, the detection algorithms that offer the best performance when discriminating falls from conventional Activities of Daily Living (ADLs) are those built on machine learning and deep learning mechanisms. In this regard, supervised machine learning binary classification methods have been massively employed by the related literature. However, the learning phase of these algorithms requires mobility patterns caused by falls, which are very difficult to obtain in realistic application scenarios. An interesting alternative is offered by One-Class Classifiers (OCCs), which can be exclusively trained and configured with movement traces of a single type (ADLs). In this paper, a systematic study of the performance of various typical OCCs (for diverse sets of input features and hyperparameters) is performed when applied to nine public repositories of falls and ADLs. The results show the potentials of these classifiers, which are capable of achieving performance metrics very similar to those of supervised algorithms (with values for the specificity and the sensitivity higher than 95%). However, the study warns of the need to have a wide variety of types of ADLs when training OCCs, since activities with a high degree of mobility can significantly increase the frequency of false alarms (ADLs identified as falls) if not considered in the data subsets used for training},
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In recent years, the popularity of wearable devices has fostered the investigation of automatic fall detection systems based on the analysis of the signals captured by transportable inertial sensors. Due to the complexity and variety of human movements, the detection algorithms that offer the best performance when discriminating falls from conventional Activities of Daily Living (ADLs) are those built on machine learning and deep learning mechanisms. In this regard, supervised machine learning binary classification methods have been massively employed by the related literature. However, the learning phase of these algorithms requires mobility patterns caused by falls, which are very difficult to obtain in realistic application scenarios. An interesting alternative is offered by One-Class Classifiers (OCCs), which can be exclusively trained and configured with movement traces of a single type (ADLs). In this paper, a systematic study of the performance of various typical OCCs (for diverse sets of input features and hyperparameters) is performed when applied to nine public repositories of falls and ADLs. The results show the potentials of these classifiers, which are capable of achieving performance metrics very similar to those of supervised algorithms (with values for the specificity and the sensitivity higher than 95%). However, the study warns of the need to have a wide variety of types of ADLs when training OCCs, since activities with a high degree of mobility can significantly increase the frequency of false alarms (ADLs identified as falls) if not considered in the data subsets used for training
Silva, Carlos A.; García-Bermúdez, Rodolfo; Casilari, Eduardo
Features Selection for Fall Detection Systems Based on Machine Learning and Accelerometer Signals Conference
Advances in Computational Intelligence 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, LNCS Springer Nature Switzerland, 2021.
@conference{Fea/2021,
title = {Features Selection for Fall Detection Systems Based on Machine Learning and Accelerometer Signals},
author = {Carlos A. Silva and Rodolfo García-Bermúdez and Eduardo Casilari},
url = {https://link.springer.com/chapter/10.1007%2F978-3-030-85099-9_31},
doi = {10.1007/978-3-030-85099-9_31},
year = {2021},
date = {2021-06-01},
booktitle = {Advances in Computational Intelligence 16th International Work-Conference on Artificial Neural Networks, IWANN 2021},
pages = {380–391},
publisher = {Springer Nature Switzerland},
series = {LNCS},
abstract = {Fall among older people is a major medical concern. Fall Detection Systems (FDSs) have been actively investigated to solve this problem. In this sense, FDSs must effectively reduce both the rates of false alarms and unnoticed fall. In this work we carry out a systematic evaluation of the performance of one of the most widely used machine learning supervised algorithm (Support Vector Machine) when using different input features. To evaluate the impact of the feature selection, we use Area Under the Curve (AUC) of Receiver Operating Characteristic (ROC) Curve as the performance metric. The results showed that with four features it is possible to obtain acceptable values for the detection of falls using accelerometer signals obtained from the userrqs waist. In addition, we also investigate if the impact of selecting the features based on the analysis of a dataset different from the final application framework where the detector will be operative.},
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Fall among older people is a major medical concern. Fall Detection Systems (FDSs) have been actively investigated to solve this problem. In this sense, FDSs must effectively reduce both the rates of false alarms and unnoticed fall. In this work we carry out a systematic evaluation of the performance of one of the most widely used machine learning supervised algorithm (Support Vector Machine) when using different input features. To evaluate the impact of the feature selection, we use Area Under the Curve (AUC) of Receiver Operating Characteristic (ROC) Curve as the performance metric. The results showed that with four features it is possible to obtain acceptable values for the detection of falls using accelerometer signals obtained from the userrqs waist. In addition, we also investigate if the impact of selecting the features based on the analysis of a dataset different from the final application framework where the detector will be operative.
González-Cañete, Francisco J.; Casilari, Eduardo
A Feasibility Study of the Use of Smartwatches in Wearable Fall Detection Systems Journal Article
In: Sensors, vol. 21, no. 6, pp. 2254, 2021, ISSN: 1424-8220.
@article{AFe/2021,
title = {A Feasibility Study of the Use of Smartwatches in Wearable Fall Detection Systems},
author = {Francisco J. González-Cañete and Eduardo Casilari},
url = {https://www.mdpi.com/1424-8220/21/6/2254},
doi = {10.3390/s21062254},
issn = {1424-8220},
year = {2021},
date = {2021-03-01},
journal = {Sensors},
volume = {21},
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2020
Casilari, Eduardo; Santoyo-Ramón, Jose Antonio; Cano-García, José Manuel
On the Heterogeneity of Existing Repositories of Movements Intended for the Evaluation of Fall Detection Systems Journal Article
In: Journal of Healthcare Engineering, vol. 2020, pp. 6622285, 2020, ISSN: 2040-2295.
@article{Ont/2020,
title = {On the Heterogeneity of Existing Repositories of Movements Intended for the Evaluation of Fall Detection Systems},
author = {Eduardo Casilari and Jose Antonio Santoyo-Ramón and José Manuel Cano-García},
url = {https://www.hindawi.com/journals/jhe/2020/6622285/},
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year = {2020},
date = {2020-12-01},
journal = {Journal of Healthcare Engineering},
volume = {2020},
pages = {6622285},
abstract = {Due to the serious impact of falls on the autonomy and health of older people, the investigation of wearable alerting systems for the automatic detection of falls has gained considerable scientific interest in the field of body telemonitoring with wireless sensors. Because of the difficulties of systematically validating these systems in a real application scenario, Fall Detection Systems (FDSs) are typically evaluated by studying their response to datasets containing inertial sensor measurements captured during the execution of labelled nonfall and fall movements. In this context, during the last decade, numerous publicly accessible databases have been released aiming at offering a common benchmarking tool for the validation of the new proposals on FDSs. This work offers a comparative and updated analysis of these existing repositories. For this purpose, the samples contained in the datasets are characterized by different statistics that model diverse aspects of the mobility of the human body in the time interval where the greatest change in the acceleration module is identified. By using one-way analysis of variance (ANOVA) on the series of these features, the comparison shows the significant differences detected between the datasets, even when comparing activities that require a similar degree of physical effort. This heterogeneity, which may result from the great variability of the sensors, experimental users, and testbeds employed to generate the datasets, is relevant because it casts doubt on the validity of the conclusions of many studies on FDSs, since most of the proposals in the literature are only evaluated using a single database.},
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Due to the serious impact of falls on the autonomy and health of older people, the investigation of wearable alerting systems for the automatic detection of falls has gained considerable scientific interest in the field of body telemonitoring with wireless sensors. Because of the difficulties of systematically validating these systems in a real application scenario, Fall Detection Systems (FDSs) are typically evaluated by studying their response to datasets containing inertial sensor measurements captured during the execution of labelled nonfall and fall movements. In this context, during the last decade, numerous publicly accessible databases have been released aiming at offering a common benchmarking tool for the validation of the new proposals on FDSs. This work offers a comparative and updated analysis of these existing repositories. For this purpose, the samples contained in the datasets are characterized by different statistics that model diverse aspects of the mobility of the human body in the time interval where the greatest change in the acceleration module is identified. By using one-way analysis of variance (ANOVA) on the series of these features, the comparison shows the significant differences detected between the datasets, even when comparing activities that require a similar degree of physical effort. This heterogeneity, which may result from the great variability of the sensors, experimental users, and testbeds employed to generate the datasets, is relevant because it casts doubt on the validity of the conclusions of many studies on FDSs, since most of the proposals in the literature are only evaluated using a single database.
Casilari, Eduardo; Lora-Rivera, Raúl; García-Lagos, Francisco
A Study on the Application of Convolutional Neural Networks to Fall Detection Evaluated with Multiple Public Datasets Journal Article
In: Sensors, vol. 20, no. 5, pp. 1466, 2020, ISSN: 1424-8220.
@article{ASt/2020,
title = {A Study on the Application of Convolutional Neural Networks to Fall Detection Evaluated with Multiple Public Datasets},
author = {Eduardo Casilari and Raúl Lora-Rivera and Francisco García-Lagos},
url = {https://www.mdpi.com/1424-8220/20/5/1466},
doi = {10.3390/s20051466},
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year = {2020},
date = {2020-03-01},
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abstract = {Due to the repercussion of falls on both the health and self-sufficiency of older people and on the financial sustainability of healthcare systems, the study of wearable fall detection systems (FDSs) has gained much attention during the last years. The core of a FDS is the algorithm that discriminates falls from conventional Activities of Daily Life (ADLs). This work presents and evaluates a convolutional deep neural network when it is applied to identify fall patterns based on the measurements collected by a transportable tri-axial accelerometer. In contrast with most works in the related literature, the evaluation is performed against a wide set of public data repositories containing the traces obtained from diverse groups of volunteers during the execution of ADLs and mimicked falls. Although the method can yield very good results when it is hyper-parameterized for a certain dataset, the global evaluation with the other repositories highlights the difficulty of extrapolating to other testbeds the network architecture that was configured and optimized for a particular dataset.},
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Due to the repercussion of falls on both the health and self-sufficiency of older people and on the financial sustainability of healthcare systems, the study of wearable fall detection systems (FDSs) has gained much attention during the last years. The core of a FDS is the algorithm that discriminates falls from conventional Activities of Daily Life (ADLs). This work presents and evaluates a convolutional deep neural network when it is applied to identify fall patterns based on the measurements collected by a transportable tri-axial accelerometer. In contrast with most works in the related literature, the evaluation is performed against a wide set of public data repositories containing the traces obtained from diverse groups of volunteers during the execution of ADLs and mimicked falls. Although the method can yield very good results when it is hyper-parameterized for a certain dataset, the global evaluation with the other repositories highlights the difficulty of extrapolating to other testbeds the network architecture that was configured and optimized for a particular dataset.
Casilari, Eduardo; Álvarez-Marco, Moisés; García-Lagos, Francisco
A Study of the Use of Gyroscope Measurements in Wearable Fall Detection Systems Journal Article
In: Symmetry, vol. 12, no. 4, pp. 649, 2020, ISSN: 2073-8994.
@article{AStgiroscopo/2020,
title = {A Study of the Use of Gyroscope Measurements in Wearable Fall Detection Systems},
author = {Eduardo Casilari and Moisés Álvarez-Marco and Francisco García-Lagos},
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Delgado-Escaño, Rubén; Castro, Francisco M.; Cózar, Julián R.; Marín-Jiménez, Manuel J.; Guil, Nicolás; Casilari, Eduardo
A cross-dataset deep learning-based classifier for people fall detection and identification Journal Article
In: Computer Methods and Programs in Biomedicine, vol. 184, no. 105265, 2020, ISSN: 0169-2607.
@article{Acr/2020,
title = {A cross-dataset deep learning-based classifier for people fall detection and identification},
author = {Rubén Delgado-Escaño and Francisco M. Castro and Julián R. Cózar and Manuel J. Marín-Jiménez and Nicolás Guil and Eduardo Casilari},
url = {https://www.sciencedirect.com/science/article/pii/S0169260719311770},
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González-Cañete, Francisco J.; Casilari, Eduardo
Consumption Analysis of Smartphone based Fall Detection Systems with Multiple External Wireless Sensors Journal Article
In: Sensors, vol. 20, no. 3, 2020, ISSN: 1424-8220.
@article{Con/2020,
title = {Consumption Analysis of Smartphone based Fall Detection Systems with Multiple External Wireless Sensors},
author = {Francisco J. González-Cañete and Eduardo Casilari},
url = {https://www.mdpi.com/1424-8220/20/3/622},
doi = {10.3390/s20030622},
issn = {1424-8220},
year = {2020},
date = {2020-01-01},
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2019
Casilari, Eduardo; García-Lagos, Francisco
A comprehensive study on the use of artificial neural networks in wearable fall detection systems Journal Article
In: Expert Systems with Applications, vol. 138, no. 112811, 2019, ISSN: 0957-4174.
@article{Aco/2019,
title = {A comprehensive study on the use of artificial neural networks in wearable fall detection systems},
author = {Eduardo Casilari and Francisco García-Lagos},
url = {https://www.sciencedirect.com/science/article/pii/S095741741930507X},
doi = {10.1016/j.eswa.2019.07.028},
issn = {0957-4174},
year = {2019},
date = {2019-12-01},
journal = {Expert Systems with Applications},
volume = {138},
number = {112811},
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Santoyo-Ramón, Jose-Antonio; Casilari, Eduardo; Cano-García, José Manuel
Study of the Detection of Falls Using the SVM Algorithm, Different Datasets of Movements and ANOVA Conference
Proceedings of IEEE IWBBIO: International Work-Conference on Bioinformatics and Biomedical Engineering, Springer, Granada (Spain), May 8-10, 2019, 2019, ISBN: 9783030179373.
@conference{Stu/2019,
title = {Study of the Detection of Falls Using the SVM Algorithm, Different Datasets of Movements and ANOVA},
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Casilari, Eduardo; Rivera, Raúl Lora; Lagos, Francisco García
Evaluation of a Fall Alerting System based on a Convolutional Deep Neural Network Conference
Proceedings of IEEE 2019 International Conference on Control, Decision and Information Technologies (CODIT’2019), París (France), April 23-26, 2019, 2019.
@conference{Eva/2019,
title = {Evaluation of a Fall Alerting System based on a Convolutional Deep Neural Network},
author = {Eduardo Casilari and Raúl Lora Rivera and Francisco García Lagos},
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booktitle = {Proceedings of IEEE 2019 International Conference on Control, Decision and Information Technologies (CODIT'2019)},
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Casilari, Eduardo; Lora-Rivera, Raúl; García-Lagos, Francisco
A Wearable Fall Detection System Using Deep Learning Conference
Proceedings of International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 2019). Advances and Trends in Artificial Intelligence. From Theory to Practice (LNCS), Graz (Austria), July 9-11, 2019, 2019, ISBN: 9783030229986.
@conference{cas/AWe/2019,
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2018
Santoyo-Ramón, Jose-Antonio; Casilari, Eduardo; Cano-García, José Manuel
Analysis of a Smartphone-Based Architecture with Multiple Mobility Sensors for Fall Detection with Supervised Learning Journal Article
In: Sensors, vol. 18, no. 4, 2018, ISSN: 1424-8220.
@article{Jos/Ana/2018,
title = {Analysis of a Smartphone-Based Architecture with Multiple Mobility Sensors for Fall Detection with Supervised Learning},
author = {Jose-Antonio Santoyo-Ramón and Eduardo Casilari and José Manuel Cano-García},
url = {http://www.mdpi.com/1424-8220/18/4/1155},
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Casilari, Eduardo; Santoyo-Ramón, Jose-Antonio; Cano-García, José Manuel
Analysis of a Public Repository for the Study of Automatic Fall Detection Algorithms Conference
Proceedings of the 5th International Workshop on Sensor-based Activity Recognition and Interaction (iWOAR 2018), Berlin (Germany), September 20-21, 2018, 2018, ISBN: 9781450364874.
@conference{Ana/2018b,
title = {Analysis of a Public Repository for the Study of Automatic Fall Detection Algorithms},
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Aguilera, Davinia Trujillo; García-Berdonés, Carmen; Martín, Juan Pedro Peña; Casilari, Eduardo
Libro de actas del XXVI Congreso Universitario de Innovación Educativa En las Enseñanzas Técnicas, Gijón (Spain), June 25-27, 2018, 2018, ISBN: 9788417445027.
@conference{Mej/2018s,
title = {Mejora de la praxis docente mediante la inclusión de actividades para el desarrollo de las capacidades metacognitivas de los estudiantes},
author = {Davinia Trujillo Aguilera and Carmen García-Berdonés and Juan Pedro Peña Martín and Eduardo Casilari},
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isbn = {9788417445027},
year = {2018},
date = {2018-01-01},
booktitle = {Libro de actas del XXVI Congreso Universitario de Innovación Educativa En las Enseñanzas Técnicas},
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address = {Gijón (Spain), June 25-27, 2018},
keywords = {},
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Ramón, José Antonio Santoyo; Casilari, Eduardo; Cano-García, José Manuel
Estudio de la detección de caídas utilizando el algoritmo SVM Conference
Actas del XXXIII Simposium Nacional de la Unión Científica Internacional de Radio (URSI 2018), Granada (Spain), September 5-7, 2018, 2018.
@conference{Est/2018b,
title = {Estudio de la detección de caídas utilizando el algoritmo SVM},
author = {José Antonio Santoyo Ramón and Eduardo Casilari and José Manuel Cano-García},
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year = {2018},
date = {2018-01-01},
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address = {Granada (Spain), September 5-7, 2018},
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Villén-Altamirano, Manuel; Casilari, Eduardo; Reyes-Lecuona, Arcadio
RESTART simulation: New approach to the importance in a two-queue tandem Jackson network Conference
12th International Workshop on Rare Event Simulation (RESIM 2018), Stockholm (Sweden), August 29-31, 2018, 2018.
@conference{RES/2018,
title = {RESTART simulation: New approach to the importance in a two-queue tandem Jackson network},
author = {Manuel Villén-Altamirano and Eduardo Casilari and Arcadio Reyes-Lecuona},
url = {https://people.kth.se/~pierren/resim2018/resim2018.html},
year = {2018},
date = {2018-01-01},
booktitle = {12th International Workshop on Rare Event Simulation (RESIM 2018)},
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2017
Casilari, Eduardo; Santoyo-Ramón, José-Antonio; Cano-García, José Manuel
Analysis of public datasets for wearable fall detection systems Journal Article
In: Sensors, vol. 17, no. 7, 2017, ISSN: 1424-8220.
@article{Edu/Ana/2017,
title = {Analysis of public datasets for wearable fall detection systems},
author = {Eduardo Casilari and José-Antonio Santoyo-Ramón and José Manuel Cano-García},
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year = {2017},
date = {2017-01-01},
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Casilari, Eduardo; Vizcaíno-Martín, Fco. Javier; Ruz, Ana Pozo; Romero-Jerez, Juan Manuel; Téllez-Labao, Concepción
Problemas de Fundamentos de Electrónica Analógica y Electrónica de Potencia Book
5ª, SPICUM, Colección Manuales, 100, Málaga, 2017, ISBN: 9788497479851.
@book{Edu/Pro/2017-y,
title = {Problemas de Fundamentos de Electrónica Analógica y Electrónica de Potencia},
author = {Eduardo Casilari and Fco. Javier Vizcaíno-Martín and Ana Pozo Ruz and Juan Manuel Romero-Jerez and Concepción Téllez-Labao},
url = {http://umaeditorial.uma.es/product/9708-problemas-de-fundamentos-de-electr%C3%B3nica-anal%C3%B3gica-y-electr%C3%B3nica-de-potencia},
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Casilari, Eduardo; Santoyo-Ramón, Jose-Antonio; Cano-García, José Manuel
UMAFall: A Multisensor Dataset for the Research on Automatic Fall Detection Conference
Proceedings of 14th International Conference on Mobile Systems and Pervasive Computing (MobiSPCrq2017) (Procedia Computer Science, 110), Leuven (Belgium), 2017.
@conference{Edu/UMA/2017,
title = {UMAFall: A Multisensor Dataset for the Research on Automatic Fall Detection},
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url = {https://www.sciencedirect.com/science/article/pii/S1877050917312899},
year = {2017},
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booktitle = {Proceedings of 14th International Conference on Mobile Systems and Pervasive Computing (MobiSPCrq2017) (Procedia Computer Science, 110)},
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2016
Casilari, Eduardo; Santoyo-Ramón, Jose-Antonio; cano,
Analysis of a smartphone-based architecture with multiple mobility sensors for fall detection Journal Article
In: PLoS one, vol. 12, no. 11, 2016.
@article{Ana/2016,
title = {Analysis of a smartphone-based architecture with multiple mobility sensors for fall detection},
author = {Eduardo Casilari and Jose-Antonio Santoyo-Ramón and cano},
url = {http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0168069},
year = {2016},
date = {2016-12-01},
journal = {PLoS one},
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García-Berdonés, Carmen; Casilari, Eduardo; Lagos, Francisco García; González-Parada, Eva; Molina-Tanco, Luis; Vizcaíno-Martín, Fco. Javier
Actas de la 24ª edición del Congreso Universitario de Innovación Educativa en las Enseñanzas Técnicas (XXIV CUIEET), Puerto Real (Spain), Septiembre 21-23, 2016, 2016.
@conference{Car/Dis/2016,
title = {Diseño de un itinerario para el desarrollo de competencias transversales en un grado de ingeniería electrónica: primeros pasos},
author = {Carmen García-Berdonés and Eduardo Casilari and Francisco García Lagos and Eva González-Parada and Luis Molina-Tanco and Fco. Javier Vizcaíno-Martín},
url = {http://riuma.uma.es/xmlui/handle/10630/12169},
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Este trabajo recoge la motivación, metodología y primeros resultados de un proyecto de innovación educativa a dos años (2015-2017) que se está llevando a cabo en la Escuela Técnica Superior de Ingeniería de Telecomunicación de la Universidad de Málaga. El objetivo fundamental del proyecto es diseñar y poner en marcha un itinerario para abordar el desarrollo de las competencias transversales a lo largo de los grados. Hasta la fecha, se han cruzado las competencias generales que la legislación vigente impone con otros marcos competenciales de especial interés, como ABET o Eur-Ace. Este cruce ha permitido seleccionar un conjunto de competencias con las que comen-zar a trabajar. El estudio de los marcos nos ha ayudado también a profundizar en la caracterización docente de cada una de ellas (resultados de aprendizaje, actividades formativas y actividades de evaluación), paso previo a establecer el orden temporal para su desarrollo. Las dificultades encontra-das en esta tarea nos han llevado a proponer un modelo de desarrollo de competencias transversales que, en fases futuras del proyecto, el profesorado usará para, coordinadamente, incorporar nuevas competencias transversales a su docencia o formalizar las que ya desarrolla.
González-Parada, Eva; Cano-García, José Manuel; Casilari, Eduardo; Martín, Juan Pedro Peña; Pérez-Rodríguez, Eduardo; Aguilera, Davinia Trujillo
Actividad extracurricular en el ámbito de la Ingeniería para la competencia genérica de comunicación Conference
Actas de la 24ª edición del Congreso Universitario de Innovación Educativa en las Enseñanzas Técnicas (XXIV CUIEET), Puerto Real (Spain), Septiembre 21-23, 2016, 2016.
@conference{Eva/Act/2016,
title = {Actividad extracurricular en el ámbito de la Ingeniería para la competencia genérica de comunicación},
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Casilari, Eduardo; Ortuño, Pablo
A Web Architecture of a Framework to evaluate Smartphone-Based Fall Detection Systems Conference
Proceedings of the 8th International Conference on e-Health, Funchal (Madeira-Portugal), July 1-3, 2016, 2016.
@conference{Edu/AWe/2016,
title = {A Web Architecture of a Framework to evaluate Smartphone-Based Fall Detection Systems},
author = {Eduardo Casilari and Pablo Ortuño},
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Casilari, Eduardo; Oviedo-Jiménez, Miguel-Ángel
Analysis of a hybrid Android system for fall detection Conference
International journal of computers and communications (Proceedings of the Conference on Systems, Control, Signal Processing and Informatics), vol. 10, Riga (Latvia), May 29-31, 2016, 2016, ISSN: 2074-1294.
@conference{Edu/Ana/2016,
title = {Analysis of a hybrid Android system for fall detection},
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url = {http://www.naun.org/cms.action?id=11961},
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booktitle = {International journal of computers and communications (Proceedings of the Conference on Systems, Control, Signal Processing and Informatics)},
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tppubtype = {conference}
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Villén-Altamirano, Manuel; Reyes-Lecuona, Arcadio; Casilari, Eduardo
Optimal Importance Function for Restart Simulation of a Two-queue Tandem Jackson Network Conference
11th International Workshop on Rare Event Simulation (RESIM 2016), Eindhoven (The Netherlands), March 29 – April 1, 2016, 2016.
@conference{Man/Opt/2016,
title = {Optimal Importance Function for Restart Simulation of a Two-queue Tandem Jackson Network},
author = {Manuel Villén-Altamirano and Arcadio Reyes-Lecuona and Eduardo Casilari},
url = {https://www.eurandom.tue.nl/events/workshops/2016/SAM_PROB+ANALYSIS/WS3.html},
year = {2016},
date = {2016-01-01},
booktitle = {11th International Workshop on Rare Event Simulation (RESIM 2016)},
address = {Eindhoven (The Netherlands), March 29 - April 1, 2016},
keywords = {},
pubstate = {published},
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2015
Luque-Giráldez, J. Rafael; Morón-Fernández, María José; Casilari, Eduardo
A Characterization of the Performance of Bluetooth 2.x+EDR Technology in Noisy Environments Journal Article
In: Wireless Networks, vol. 21, no. 6, 2015, ISSN: 1022-0038.
@article{ACh/2015,
title = {A Characterization of the Performance of Bluetooth 2.x+EDR Technology in Noisy Environments},
author = {J. Rafael Luque-Giráldez and María José Morón-Fernández and Eduardo Casilari},
url = {https://link.springer.com/article/10.1007/s11276-015-0888-1},
doi = {10.1007/s11276-015-0888-1},
issn = {1022-0038},
year = {2015},
date = {2015-08-01},
journal = {Wireless Networks},
volume = {21},
number = {6},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Casilari, Eduardo; Luque-Giráldez, J. Rafael; Morón-Fernández, María José
Analysis of Android Device-based Solutions for Fall Detection Journal Article
In: Sensors, vol. 15, no. 8, pp. 17827–17894, 2015, ISSN: 1424-8220.
@article{Ana,
title = {Analysis of Android Device-based Solutions for Fall Detection},
author = {Eduardo Casilari and J. Rafael Luque-Giráldez and María José Morón-Fernández},
url = {http://www.mdpi.com/1424-8220/15/8/17827},
doi = {10.3390/s150817827},
issn = {1424-8220},
year = {2015},
date = {2015-07-01},
journal = {Sensors},
volume = {15},
number = {8},
pages = {17827–17894},
keywords = {},
pubstate = {published},
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Casilari, Eduardo; Oviedo-Jiménez, Miguel-Ángel
Automatic Fall Detection System Based on the Combined Use of a Smartphone and a Smartwatch Journal Article
In: PLoS ONE, vol. 10, no. 11, pp. e0140929, 2015, ISSN: 1544-9173.
@article{Edu/Aut/2015,
title = {Automatic Fall Detection System Based on the Combined Use of a Smartphone and a Smartwatch},
author = {Eduardo Casilari and Miguel-Ángel Oviedo-Jiménez},
url = {http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0140929},
issn = {1544-9173},
year = {2015},
date = {2015-01-01},
journal = {PLoS ONE},
volume = {10},
number = {11},
pages = {e0140929},
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pubstate = {published},
tppubtype = {article}
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2014
González-Cañete, Francisco J.; Casilari, Eduardo
Review on the Simulation of Cooperative Caching Schemes for MANETs Conference
Proceedings of the 2nd International Conference on Wireless and Mobile Communication Systems (WMCS ’14), Lisbon (Portugal), October 30- Nov 1, 2014, 2014.
@conference{Fra/Rev/2015,
title = {Review on the Simulation of Cooperative Caching Schemes for MANETs},
author = {Francisco J. González-Cañete and Eduardo Casilari},
url = {https://riuma.uma.es/xmlui/bitstream/handle/10630/8381/wseas-full.pdf?sequence=3},
year = {2014},
date = {2014-10-01},
booktitle = {Proceedings of the 2nd International Conference on Wireless and Mobile Communication Systems (WMCS '14)},
pages = {140–149},
address = {Lisbon (Portugal), October 30- Nov 1, 2014},
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Altamirano, Manolo Villén; Casilari, Eduardo; Reyes-Lecuona, Arcadio
New concept of importance in RESTART simulations Conference
10th International Workshop on Rare Event Simulation (RESIM 2014), Amsterdam (The Netherlands), August 27-29, 2014, 2014.
@conference{New/2014,
title = {New concept of importance in RESTART simulations},
author = {Manolo Villén Altamirano and Eduardo Casilari and Arcadio Reyes-Lecuona},
url = {https://www.researchgate.net/publication/265384522_Working_Paper_NEW_CONCEPT_OF_IMPORTANCE_IN_RESTART_SIMULATIONS},
year = {2014},
date = {2014-08-01},
booktitle = {10th International Workshop on Rare Event Simulation (RESIM 2014)},
address = {Amsterdam (The Netherlands), August 27-29, 2014},
abstract = {RESTART is a widely applicable accelerated simulation technique that allows the evaluation of extremely low probabilities. In this method, a number of simulation retrials are performed when the process enters regions of the state space where the chance of occurrence of a rare event of interest is higher. In previous papers the importance of a state, which is a measure of the chance of occurrence of the rare event when the state occurs, was defined. The mentioned regions should be defined by means of the importance of the states but, due to the difficulty of knowing them, they are defined by means of another function of the states called the importance function. The choice by the user of an importance function which reflects the importance of the states is crucial for the effective application of RESTART. The problem of the previous definition of importance is that the importance of a state does not only depend on the state itself but also on the chosen importance function. It produces a loop between importance and importance function which can make more difficult to find an appropriate importance function. The paper presents a new concept of importance which does not depend on the chosen importance function. It avoids the above mentioned loop and can make easier to find an appropriate importance function. The paper also presents the application of this new concept of importance to an M/M/1 queue and the work progress of its application to a two-queue Jackson tandem network.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
RESTART is a widely applicable accelerated simulation technique that allows the evaluation of extremely low probabilities. In this method, a number of simulation retrials are performed when the process enters regions of the state space where the chance of occurrence of a rare event of interest is higher. In previous papers the importance of a state, which is a measure of the chance of occurrence of the rare event when the state occurs, was defined. The mentioned regions should be defined by means of the importance of the states but, due to the difficulty of knowing them, they are defined by means of another function of the states called the importance function. The choice by the user of an importance function which reflects the importance of the states is crucial for the effective application of RESTART. The problem of the previous definition of importance is that the importance of a state does not only depend on the state itself but also on the chosen importance function. It produces a loop between importance and importance function which can make more difficult to find an appropriate importance function. The paper presents a new concept of importance which does not depend on the chosen importance function. It avoids the above mentioned loop and can make easier to find an appropriate importance function. The paper also presents the application of this new concept of importance to an M/M/1 queue and the work progress of its application to a two-queue Jackson tandem network.
Luque-Giráldez, J. Rafael; Morón-Fernández, María José; Casilari, Eduardo
On the Capability of Smartphones to Perform as Communication Gateways in Medical Wireless Personal Area Networks Journal Article
In: Sensors, vol. 14, no. 1, pp. 575–594, 2014, ISSN: 1424-8220.
@article{JRa/Ont,
title = {On the Capability of Smartphones to Perform as Communication Gateways in Medical Wireless Personal Area Networks},
author = {J. Rafael Luque-Giráldez and María José Morón-Fernández and Eduardo Casilari},
url = {http://www.mdpi.com/1424-8220/14/1/575},
doi = {10.3390/s140100575},
issn = {1424-8220},
year = {2014},
date = {2014-01-01},
journal = {Sensors},
volume = {14},
number = {1},
pages = {575–594},
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Luque-Giráldez, J. Rafael; Casilari, Eduardo; Morón-Fernández, María José; Redondo, Gema
Comparison and Characterization of Android-Based Fall Detection Systems Journal Article
In: Sensors, vol. 14, no. 10, pp. 18543–18574, 2014, ISSN: 1424-8220.
@article{JRa/Com/2014,
title = {Comparison and Characterization of Android-Based Fall Detection Systems},
author = {J. Rafael Luque-Giráldez and Eduardo Casilari and María José Morón-Fernández and Gema Redondo},
url = {http://webpersonal.uma.es/de/ECASILARI/pagina.html},
issn = {1424-8220},
year = {2014},
date = {2014-01-01},
journal = {Sensors},
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number = {10},
pages = {18543–18574},
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2013
López, Javier Hurtado; Casilari, Eduardo
An Adaptive Algorithm to Optimize the Dynamics of IEEE 802.15.4 Networks Conference
Proceedings of the 5th International Conference on Mobile Networks and Management (MONAMIrq2013), Cork (Ireland), September 23-25, 2013, 2013.
@conference{Jav/AnA/2013,
title = {An Adaptive Algorithm to Optimize the Dynamics of IEEE 802.15.4 Networks},
author = {Javier Hurtado López and Eduardo Casilari},
url = {https://link.springer.com/chapter/10.1007/978-3-319-04277-0_11},
year = {2013},
date = {2013-09-01},
booktitle = {Proceedings of the 5th International Conference on Mobile Networks and Management (MONAMIrq2013)},
pages = {136–148},
address = {Cork (Ireland), September 23-25, 2013},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Triviño-Cabrera, Alicia; Quintana, Alfonso Ariza; Casilari, Eduardo; Cano-Escribá, Juan-Carlos
Cooperative Layer-2 Based Routing Approach for Hybrid Wireless Mesh Networks Journal Article
In: China Communications, vol. 10, no. 8, pp. 88–99, 2013, ISSN: 1673-5447.
@article{Coo/2013,
title = {Cooperative Layer-2 Based Routing Approach for Hybrid Wireless Mesh Networks},
author = {Alicia Triviño-Cabrera and Alfonso Ariza Quintana and Eduardo Casilari and Juan-Carlos Cano-Escribá},
url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6633748&tag=1},
doi = {10.1109/CC.2013.6633748},
issn = {1673-5447},
year = {2013},
date = {2013-08-01},
journal = {China Communications},
volume = {10},
number = {8},
pages = {88–99},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
González-Cañete, Francisco J.; Casilari, Eduardo; Triviño-Cabrera, Alicia
Cross-Layer Interception Caching for MANETs Journal Article
In: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST), vol. 111, pp. 196–213, 2013.
@article{Fra/Cro/2013,
title = {Cross-Layer Interception Caching for MANETs},
author = {Francisco J. González-Cañete and Eduardo Casilari and Alicia Triviño-Cabrera},
year = {2013},
date = {2013-01-01},
journal = {Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST)},
volume = {111},
pages = {196–213},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Yuste-Delgado, Antonio-Jesús; Triviño-Cabrera, Alicia; Casilari, Eduardo
Type-2 fuzzy decision support system to optimise MANET integration into infrastructure-based wireless systems Journal Article
In: Expert Systems with Applications, vol. 40, no. 7, pp. 2552–2567, 2013, ISSN: 09574174.
@article{Yuste20132552,
title = {Type-2 fuzzy decision support system to optimise MANET integration into infrastructure-based wireless systems},
author = {Antonio-Jesús Yuste-Delgado and Alicia Triviño-Cabrera and Eduardo Casilari},
doi = {10.1016/j.eswa.2012.10.063},
issn = {09574174},
year = {2013},
date = {2013-01-01},
journal = {Expert Systems with Applications},
volume = {40},
number = {7},
pages = {2552–2567},
abstract = {Mobile ad hoc networks are able to extend the coverage area of Internet access points by establishing multihop communication paths. Due to diverse factors such as the mobility of the nodes, the propagation conditions or the traffic status, the communication paths present a lifetime. In fact, the quality of the Internet connection mainly depends on the durability of the employed communication routes. In order to improve the network performance, the nodes should select the best route in terms of its remaining lifetime. Since the factors impacting the route lifetime are unpredictable, the route remaining lifetime cannot be analytically derived. Under these circumstances, a fuzzy-logic system outstands as a potential solution to estimate the stability of the routes. This paper analyses the potentiality of this kind of solution. In particular, the paper presents a fuzzy logic system which should be installed in the mobile nodes to distributedly identify the stable routes. In particular, the system is supported by an interval-based type-2 fuzzy logic. Being a type-2 fuzzy logic system, it is able to cope with inexact estimations. This ability is necessary to avoid the use of additional messages which will occupy the scarce wireless medium. On the other hand, an interval-based fuzzy system provides the simplicity demanded by the energy-constrained mobile devices. As a novelty, the two outputs of the interval-based fuzzy system are employed. The use of each output depends on the traffic state of the mobile node. By means of extensive simulations, we demonstrate the goodness of the proposed system. © 2012 Elsevier B.V. All rights reserved.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mobile ad hoc networks are able to extend the coverage area of Internet access points by establishing multihop communication paths. Due to diverse factors such as the mobility of the nodes, the propagation conditions or the traffic status, the communication paths present a lifetime. In fact, the quality of the Internet connection mainly depends on the durability of the employed communication routes. In order to improve the network performance, the nodes should select the best route in terms of its remaining lifetime. Since the factors impacting the route lifetime are unpredictable, the route remaining lifetime cannot be analytically derived. Under these circumstances, a fuzzy-logic system outstands as a potential solution to estimate the stability of the routes. This paper analyses the potentiality of this kind of solution. In particular, the paper presents a fuzzy logic system which should be installed in the mobile nodes to distributedly identify the stable routes. In particular, the system is supported by an interval-based type-2 fuzzy logic. Being a type-2 fuzzy logic system, it is able to cope with inexact estimations. This ability is necessary to avoid the use of additional messages which will occupy the scarce wireless medium. On the other hand, an interval-based fuzzy system provides the simplicity demanded by the energy-constrained mobile devices. As a novelty, the two outputs of the interval-based fuzzy system are employed. The use of each output depends on the traffic state of the mobile node. By means of extensive simulations, we demonstrate the goodness of the proposed system. © 2012 Elsevier B.V. All rights reserved.
González-Cañete, Francisco J.; Casilari, Eduardo
A Study of the Performance of Cooperative Caching in Static Ad Hoc Networks Journal Article
In: International Journal on Advances in Networks and Services, vol. 6, no. 1 & 2, pp. 68–79, 2013.
@article{ASt/2013,
title = {A Study of the Performance of Cooperative Caching in Static Ad Hoc Networks},
author = {Francisco J. González-Cañete and Eduardo Casilari},
year = {2013},
date = {2013-01-01},
journal = {International Journal on Advances in Networks and Services},
volume = {6},
number = {1 & 2},
pages = {68–79},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Cano-García, José Manuel; Casilari, Eduardo; González-Parada, Eva
An empirical study on the performance of bluetooth scatternets Conference
Proceedings of the 9th International Wireless Communications and Mobile Computing Conference (IWCMC 2013), Cagliari (Italy), July 1-5, 2013, 2013.
@conference{Jos/Ane/2013,
title = {An empirical study on the performance of bluetooth scatternets},
author = {José Manuel Cano-García and Eduardo Casilari and Eva González-Parada},
url = {https://ieeexplore.ieee.org/document/6583696/},
doi = {10.1109/IWCMC.2013.6583696},
year = {2013},
date = {2013-01-01},
booktitle = {Proceedings of the 9th International Wireless Communications and Mobile Computing Conference (IWCMC 2013)},
pages = {1017–1022},
address = {Cagliari (Italy), July 1-5, 2013},
keywords = {},
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tppubtype = {conference}
}
2012
González-Cañete, Francisco J.; Casilari, Eduardo; Triviño-Cabrera, Alicia
Cross-layer Interception Caching for MANETs Conference
Proceedings of the 4th International Conference on Ad Hoc Networks (AdHocNets 2012), Paris (France), October 16-17, 2012, 2012.
@conference{Fra/Cro/2012,
title = {Cross-layer Interception Caching for MANETs},
author = {Francisco J. González-Cañete and Eduardo Casilari and Alicia Triviño-Cabrera},
url = {https://link.springer.com/chapter/10.1007/978-3-642-36958-2_14},
doi = {10.1007/978-3-642-36958-2_14},
year = {2012},
date = {2012-10-01},
booktitle = {Proceedings of the 4th International Conference on Ad Hoc Networks (AdHocNets 2012)},
address = {Paris (France), October 16-17, 2012},
keywords = {},
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}