A Comparative Study on the Suitability of Smartphones and IMU for Mobile, Unsupervised Energy Expenditure Calculi

The metabolic equivalent of task (MET) is currently the most used indicator for measuring the energy expenditure (EE) of a physical activity (PA) and has become an important measure for determining and supervising a person’s state of health. The use of new devices which are capable of measuring inertial movements by means of built-in accelerometers enable the PA to be measured objectively on the basis of the reckoning of “counts”. These devices are also known as inertial measurement units (IMUs) and each count is an aggregated value indicating the intensity of a movement and can be used in conjunction with other parameters to determine the MET rate of a particular physical activity and thus it’s associated EE. Various types of inertial devices currently exist that enable count calculus and physical activity to be monitored. The advent of mobile devices, such as smartphones, with empowered computation capabilities and integrated inertial sensors, has enabled EE to be measure in a distributed, ubiquitous and natural way, thereby overcoming the reluctance of users and practitioners associated with in-lab studies. From the point of view of the process analysis and infrastructure needed to manage data from inertial devices, there are also various differences in count computing: extra devices are required, out-of-device processing, etc. This paper presents a study to discover whether the estimation of energy expenditure is dependent on the accelerometer of the device used in measurements and to discover the suitability of each device for performing certain physical activities. In order to achieve this objective, we have conducted several experiments with different subjects on the basis of the performance of various daily activities with different smartphones and IMUs.This research work was partially supported by the project ‘Sistema Ergonómico Integral para la evaluación de la locomoción como predictor de la calidad de vida relacionada con la salud en Mayores (Ergoloc)’, funded by the Spanish Ministry of Economy and Competitiveness under the project DEP2012-40069; Facultad de Educación, Economía y Tecnología de Ceuta under the “Contrato-programa” of research for the period 2013–2015 and by the Programa de Fortalecimiento de I+D+i de la Universidad de Granada 2014-15. The Ministry of Education, Culture and Sports of Spain supported the work of Orantes-González, E. (ref. FPU13/00162). The authors would also like to acknowledge contribution from COST Action IC1303

General Architecture for Development of Virtual Coaches for Healthy Habits Monitoring and Encouragement

Good health is the result of a healthy lifestyle, where caring about physical activity and nutrition are key concerns. However, in today’s society, nutritional disorders are becoming increasingly frequent, affecting children, adults, and elderly people, mainly due to limited nutrition knowledge and the lack of a healthy lifestyle. A commonly adopted therapy to these imbalances is to monitor physical activity and daily habits, such as recording exercise or creating custom meal plans to count the amount of macronutrients and micronutrients acquired in each meal. Nowadays, many health tracking applications (HTA) have been developed that, for instance, record energy intake as well as users’ physiological parameters, or measure the physical activity during the day. However, most existing HTA do not have a uniform architectural design on top of which to build other applications and services. In this manuscript, we present system architecture intended to serve as a reference architecture for building HTA solutions. In order to validate the proposed architecture, we performed a preliminary evaluation with 15 well recognized experts in systems and software architecture from different entities around world and who have estimated that our proposal can generate architecture for HTA that is adequate, reliable, secure, modifiable, portable, functional, and with high conceptual integrity. In order to show the applicability of the architecture in different HTA, we developed two telemonitoring systems based on it, targeted to different tasks: nutritional coaching (Food4Living) and physical exercise coaching (TrainME). The purpose was to illustrate the kind of end-user monitoring applications that could be developed. Keywords: telemonitoring; healthy habits; virtual coaches; system

Una contribución a la evaluación de la adherencia a hábitos de vida saludables basado en aplicaciones móviles

The adherence to a healthy lifestyle plays a key role for increasing life expectancy and living better. The main habits of healthy lifestyle are: physical activity, diet and sleep quality. Nowadays, many people use a smartphone and carry it all day. The objective of this thesis is to demonstrate the feasibility of the evaluation of the adherence to a healthy lifestyle by means of smartphone applications and sensors, whether internal or externally connected. On the one hand, the accelerometer sensor is used to evaluate the physical activity and the associated energy expenditure. In previous research, we can found classifiers of physical activity from data of this sensor but the measurements were performed in a laboratory environment or with smartphone fixed to a specific position. From the collected data during a week of 26 subjects, a 75.6% of F1-score of the classification of activities has been achieved and a 3.18% of error in the energy expenditure estimation. On the other hand, the heart rate variability (HRV) can serve as indicator of behaviours related to health and physical condition. A system has been designed to evaluate the HRV using the rear camera of the smartphone as a sensor. For this purpose, the photoplethysmography technique has been used. In previous research, this technique has been used in smartphones in order to obtain the heart rate but it has not been assessed the beat-to-beat HRV. The proposed system uses the GPU for image processing in real time. The obtained results have been compared with the electrocardiogram and with a reference photoplethysmography device. For that, the standard deviation of error made for the beat detection and the level of agreement of HRV indices have been assessed. This assessment has been performed with 23 subjects and the results obtained for two different smartphone models have been compared. The standard deviation of error of heart rate detection between smartphone and electrocardiogram obtained was 5.4 ms, while between electrocardiogram and reference photoplethysmography device was 4.9 ms. On the other hand, an application for the ensemble analysis of physical activity and heart rate has been developed. Using this application, the data of 11 people was collected, they have divided in two groups of 5 and 6 people during 3 and 6 weeks respectively. From the analysis of the collected data, it has been found that the level of physical activity decreases over the time and there is some association between the constancy of the practice of physical activity and changes in mood. However, these association should be taken with caution due to the reduced number of subjects which were involved in this study. Therefore, the developed system is a starting point in order to evaluate the adherence to a healthy lifestyle in a unified way with an single application. Finally, one of the consequences of leading an unhealthy lifestyle is the decreasing of quality of sleep that can cause daytime sleepiness. This can be a serious health risk, for example if it occurs while driving. To prevent this, an early drowsiness detection system based on the analysis of respiratory signal and respiratory rate variability has been proposed and validated. The designed algorithm has been assessed with 15 subjects and a specificity of 96.6% and a sensitivity of 90.3% has been obtained.La adherencia a un estilo de vida saludable es un factor muy importante para alargar años de vida y aumentar su calidad. Los principales hábitos de vida saludable son: la actividad física, la dieta y la calidad del sueño. Hoy en día muchas personas utilizan un smartphone y lo llevan encima todo el día. El objetivo de esta tesis es demostrar la viabilidad de la evaluación de la adherencia a hábitos de vida saludables mediante aplicaciones móviles y sensores ya sean del propio smartphone o conectados externamente. Para ello, se utiliza el sensor de acelerometría para evaluar la actividad física y el gasto calórico asociado. En trabajos previos podemos encontrar clasificadores de actividad física a partir de los datos de estos sensores pero las medidas las realizan en un entorno de laboratorio o con el smartphone ubicado en una posición determinada. A partir de los datos de 26 sujetos recogidos durante una semana se ha alcanzado un 75.6% de F1-score de la clasificación de actividades y un 3.18% de error de estimación de gasto calórico. Por otro lado, la variabilidad de la frecuencia cardíaca (VFC) puede servir de indicador de conductas relacionadas con la salud y la condición física. Se ha diseñado un sistema para evaluar la VFC utilizando como sensor la cámara trasera del smartphone. Para ello se ha utilizado la técnica de fotopletismografía. En trabajos previos se ha utilizado esta técnica en smartphones para obtener el ritmo cardíaco pero no se ha comparado la variabilidad del ritmo cardíaco latido a latido. El sistema propuesto utiliza la GPU para procesar la imágenes en tiempo real. Los resultados obtenidos se han comparado con el electrocardiograma y con un dispositivo de fotopletismografía de referencia. Para ello, se ha evaluado la desviación estándar del error cometido en la detección del latido cardíaco y el grado de acuerdo de los índices de VFC. Esta evaluación se ha realizado en 23 sujetos y se han comparado los resultados obtenidos con dos modelos de smartphone. La desviación estándar del error en la detección del latido cardíaco obtenida entre el smartphone y el electrocardiograma es de 5.4 ms, mientras que entre el dispositivo de referencia de fotopletismografía y el electrocardiograma es de 4.9 ms. Por otro lado, se ha desarrollado una aplicación para el análisis conjunto de la actividad física y el ritmo cardíaco. Se recogieron los datos de 11 personas utilizando esta aplicación, divididas en dos grupos de 5 y 6 personas durante 3 y 6 semanas respectivamente. A partir del análisis de los datos recogidos se ha encontrado que el nivel de la actividad física desciende a lo largo del tiempo y que existe alguna asociación entre la constancia en la práctica de la actividad física y los cambios en el estado de ánimo. Sin embargo, estas asociaciones se han de tomar con precaución debido al reducido número de sujetos que han participado en este estudio. Por lo tanto, el sistema desarrollado supone un punto de partida para evaluar la adherencia a un estilo de vida saludable de forma unificada en una única aplicación. Finalmente, una de las consecuencias de llevar un estilo de vida poco saludable es el empobrecimiento de la calidad del sueño que puede provocar la somnolencia diurna. Esto puede resultar un grave peligro para la salud, por ejemplo si se produce mientras se está al volante. Para prevenir esto, se ha propuesto y validado un sistema de detección de somnolencia temprana a partir del análisis de la señal respiratoria basado en la variabilidad del ritmo respiratorio. El algoritmo diseñado ha sido validado con 15 sujetos y se ha obtenido una especificidad del 96.6% y una sensibilidad del 90.3%.Postprint (published version

Una contribución a la evaluación de la adherencia a hábitos de vida saludables basado en aplicaciones móviles

The adherence to a healthy lifestyle plays a key role for increasing life expectancy and living better. The main habits of healthy lifestyle are: physical activity, diet and sleep quality. Nowadays, many people use a smartphone and carry it all day. The objective of this thesis is to demonstrate the feasibility of the evaluation of the adherence to a healthy lifestyle by means of smartphone applications and sensors, whether internal or externally connected. On the one hand, the accelerometer sensor is used to evaluate the physical activity and the associated energy expenditure. In previous research, we can found classifiers of physical activity from data of this sensor but the measurements were performed in a laboratory environment or with smartphone fixed to a specific position. From the collected data during a week of 26 subjects, a 75.6% of F1-score of the classification of activities has been achieved and a 3.18% of error in the energy expenditure estimation. On the other hand, the heart rate variability (HRV) can serve as indicator of behaviours related to health and physical condition. A system has been designed to evaluate the HRV using the rear camera of the smartphone as a sensor. For this purpose, the photoplethysmography technique has been used. In previous research, this technique has been used in smartphones in order to obtain the heart rate but it has not been assessed the beat-to-beat HRV. The proposed system uses the GPU for image processing in real time. The obtained results have been compared with the electrocardiogram and with a reference photoplethysmography device. For that, the standard deviation of error made for the beat detection and the level of agreement of HRV indices have been assessed. This assessment has been performed with 23 subjects and the results obtained for two different smartphone models have been compared. The standard deviation of error of heart rate detection between smartphone and electrocardiogram obtained was 5.4 ms, while between electrocardiogram and reference photoplethysmography device was 4.9 ms. On the other hand, an application for the ensemble analysis of physical activity and heart rate has been developed. Using this application, the data of 11 people was collected, they have divided in two groups of 5 and 6 people during 3 and 6 weeks respectively. From the analysis of the collected data, it has been found that the level of physical activity decreases over the time and there is some association between the constancy of the practice of physical activity and changes in mood. However, these association should be taken with caution due to the reduced number of subjects which were involved in this study. Therefore, the developed system is a starting point in order to evaluate the adherence to a healthy lifestyle in a unified way with an single application. Finally, one of the consequences of leading an unhealthy lifestyle is the decreasing of quality of sleep that can cause daytime sleepiness. This can be a serious health risk, for example if it occurs while driving. To prevent this, an early drowsiness detection system based on the analysis of respiratory signal and respiratory rate variability has been proposed and validated. The designed algorithm has been assessed with 15 subjects and a specificity of 96.6% and a sensitivity of 90.3% has been obtained.La adherencia a un estilo de vida saludable es un factor muy importante para alargar años de vida y aumentar su calidad. Los principales hábitos de vida saludable son: la actividad física, la dieta y la calidad del sueño. Hoy en día muchas personas utilizan un smartphone y lo llevan encima todo el día. El objetivo de esta tesis es demostrar la viabilidad de la evaluación de la adherencia a hábitos de vida saludables mediante aplicaciones móviles y sensores ya sean del propio smartphone o conectados externamente. Para ello, se utiliza el sensor de acelerometría para evaluar la actividad física y el gasto calórico asociado. En trabajos previos podemos encontrar clasificadores de actividad física a partir de los datos de estos sensores pero las medidas las realizan en un entorno de laboratorio o con el smartphone ubicado en una posición determinada. A partir de los datos de 26 sujetos recogidos durante una semana se ha alcanzado un 75.6% de F1-score de la clasificación de actividades y un 3.18% de error de estimación de gasto calórico. Por otro lado, la variabilidad de la frecuencia cardíaca (VFC) puede servir de indicador de conductas relacionadas con la salud y la condición física. Se ha diseñado un sistema para evaluar la VFC utilizando como sensor la cámara trasera del smartphone. Para ello se ha utilizado la técnica de fotopletismografía. En trabajos previos se ha utilizado esta técnica en smartphones para obtener el ritmo cardíaco pero no se ha comparado la variabilidad del ritmo cardíaco latido a latido. El sistema propuesto utiliza la GPU para procesar la imágenes en tiempo real. Los resultados obtenidos se han comparado con el electrocardiograma y con un dispositivo de fotopletismografía de referencia. Para ello, se ha evaluado la desviación estándar del error cometido en la detección del latido cardíaco y el grado de acuerdo de los índices de VFC. Esta evaluación se ha realizado en 23 sujetos y se han comparado los resultados obtenidos con dos modelos de smartphone. La desviación estándar del error en la detección del latido cardíaco obtenida entre el smartphone y el electrocardiograma es de 5.4 ms, mientras que entre el dispositivo de referencia de fotopletismografía y el electrocardiograma es de 4.9 ms. Por otro lado, se ha desarrollado una aplicación para el análisis conjunto de la actividad física y el ritmo cardíaco. Se recogieron los datos de 11 personas utilizando esta aplicación, divididas en dos grupos de 5 y 6 personas durante 3 y 6 semanas respectivamente. A partir del análisis de los datos recogidos se ha encontrado que el nivel de la actividad física desciende a lo largo del tiempo y que existe alguna asociación entre la constancia en la práctica de la actividad física y los cambios en el estado de ánimo. Sin embargo, estas asociaciones se han de tomar con precaución debido al reducido número de sujetos que han participado en este estudio. Por lo tanto, el sistema desarrollado supone un punto de partida para evaluar la adherencia a un estilo de vida saludable de forma unificada en una única aplicación. Finalmente, una de las consecuencias de llevar un estilo de vida poco saludable es el empobrecimiento de la calidad del sueño que puede provocar la somnolencia diurna. Esto puede resultar un grave peligro para la salud, por ejemplo si se produce mientras se está al volante. Para prevenir esto, se ha propuesto y validado un sistema de detección de somnolencia temprana a partir del análisis de la señal respiratoria basado en la variabilidad del ritmo respiratorio. El algoritmo diseñado ha sido validado con 15 sujetos y se ha obtenido una especificidad del 96.6% y una sensibilidad del 90.3%

A Comparative Study on the Suitability of Smartphones and IMU for Mobile, Unsupervised Energy Expenditure Calculi

The metabolic equivalent of task (MET) is currently the most used indicator for measuring the energy expenditure (EE) of a physical activity (PA) and has become an important measure for determining and supervising a person’s state of health. The use of new devices which are capable of measuring inertial movements by means of built-in accelerometers enable the PA to be measured objectively on the basis of the reckoning of “counts”. These devices are also known as inertial measurement units (IMUs) and each count is an aggregated value indicating the intensity of a movement and can be used in conjunction with other parameters to determine the MET rate of a particular physical activity and thus it’s associated EE. Various types of inertial devices currently exist that enable count calculus and physical activity to be monitored. The advent of mobile devices, such as smartphones, with empowered computation capabilities and integrated inertial sensors, has enabled EE to be measure in a distributed, ubiquitous and natural way, thereby overcoming the reluctance of users and practitioners associated with in-lab studies. From the point of view of the process analysis and infrastructure needed to manage data from inertial devices, there are also various differences in count computing: extra devices are required, out-of-device processing, etc. This paper presents a study to discover whether the estimation of energy expenditure is dependent on the accelerometer of the device used in measurements and to discover the suitability of each device for performing certain physical activities. In order to achieve this objective, we have conducted several experiments with different subjects on the basis of the performance of various daily activities with different smartphones and IMUs

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen