A context-aware application to increase elderly users compliance with physical rehabilitation exercises at home via animatronic biofeedback

Biofeedback from physical rehabilitation exercises has proved to lead to faster recovery, better outcomes, and increased patient motivation. In addition, it allows the physical rehabilitation processes carried out at the clinic to be complemented with exercises performed at home. However, currently existing approaches rely mostly on audio and visual reinforcement cues, usually presented to the user on a computer screen or a mobile phone interface. Some users, such as elderly people, can experience difficulties to use and understand these interfaces, leading to non-compliance with the rehabilitation exercises. To overcome this barrier, latest biosignal technologies can be used to enhance the efficacy of the biofeedback, decreasing the complexity of the user interface. In this paper we propose and validate a context-aware framework for the use of animatronic biofeedback, as a way of potentially increasing the compliance of elderly users with physical rehabilitation exercises performed at home. In the scope of our work, animatronic biofeedback entails the use of pre-programmed actions on a robot that are triggered in response to certain changes detected in the users biomechanical or electrophysiological signals. We use electromyographic and accelerometer signals, collected in real time, to monitor the performance of the user while executing the exercises, and a mobile robot to provide animatronic reinforcement cues associated with their correct or incorrect execution. A context-aware application running on a smartphone aggregates the sensor data and controls the animatronic feedback. The acceptability of the animatronic biofeedback has been tested on a set of volunteer elderly users, and results suggest that the participants found the animatronic feedback engaging and of added value

A Review of Commercial and Medical-Grade Physiological Monitoring Devices for Biofeedback-Assisted Quality of Life Improvement Studies

With the rise in wearable technology and "health culture", we are seeing an increasing interest and affordances in studying how to not only prolong life expectancy but also in how to improve individuals' quality of life. On the one hand, this attempts to give meaning to the increasing life expectancy, as living above a certain threshold of pain and lack of autonomy or mobility is both degrading and unfair. On the other hand, it lowers the cost of continuous care, as individuals with high quality of life indexes tend to have lower hospital readmissions or secondary complications, not to mention higher physical and mental health. In this paper, we evaluate the current state of the art in physiological therapy (biofeedback) along with the existing medical grade and consumer grade hardware for physiological research. We provide a quick primer on the most commonly monitored physiologic metrics, as well as a brief discussion on the current state of the art in biofeedback-assisted medical applications. We then go on to present a comparative analysis between medical and consumer grade biofeedback devices and discuss the hardware specifications and potential practical applications of each consumer grade device in terms of functionality and adaptability for controlled (laboratory) and uncontrolled (field) studies. We end this article with some empirical observations based on our study so that readers might use take them into consideration when arranging a laboratory or real-world experience, thus avoiding costly time delays and material expenditures.info:eu-repo/semantics/publishedVersio

A framework for abstraction and virtualization of sensors in mobile context-aware computing

110 p.[EN] The latest mobile devices available nowadays are leading to the development of a new generation of mobile applications that are able to react to context. Context- awareness requires data from the environment, usually collected by means of sensors embedded in mobile devices or connected to them through wireless networks. Developers of mobile applications are faced with several challenges when it comes to the creation of context-aware applications. Sensor and device heterogeneity stand out among these challenges. In order to assist designers, we propose a layered conceptual framework for sensor abstraction and virtualization, called Igerri. Its main objective is to facilitate the development of context-aware applications independently of the specific sensors available in the user environment. To avoid the need to directly manage physical sensors, a layered structure of virtual and abstract sensors is conceived. Two software components, based on the proposed framework, have been designed in order to test Igerris robustness. The first one processes the information from the successive sensor layers and generates high-level context information. The second is responsible for managing network aspects and real time settings. This implementation has been tested using a representative context-aware application in different scenarios. The results obtained show that the implementation, and therefore the conceptual framework, is suitable for dealing with context information and hiding sensor programming.[EU] Gaur egungo gailu mugikor puntakoenek inguruneari erantzuteko gai diren aplikazio mugikorren garapenean oinarritzen dira. Testuingurua nabaritzeko ingurunearen informazioa behar da, zeina gailu mugikorretan txertatutako sentsoreen edo haririk gabeko sareen bitartez biltzen den. Aplikazio mugikorren garatzaileek erronka askori aurre egin behar izaten diete testuingurua kontuan hartzen duten aplikazioak garatzerakoan. Erronka na- gusien artean, sentsoreen eta gailuen heterogeneotasuna izaten dira. Garatzaileei laguntzeko asmoz, Igerri izeneko sentsoreen abstrakzio eta birtualizaziorako marko kontzeptual bat proposatzen dugu. Bere helburu nagusia, testuinguruaren aplikazio hautemangarrien garapena erraztea da, erabiltzailearen ingurunean dauden sentsore espezifikoak edozein direla ere. Sentsore fisikoak zuzenean ma- nipulatu behar izatea saihesteko, sentsore birtual eta abstraktuen egitura bat asmatu da. Igerri-ren sendotasuna egiaztatzeko, proposatutako markoan oinarritutako bi software osagai diseinatu dira. Lehenak, sentsore geruzen informazio geruzak prozesatu eta maila altuko testuinguru informazioa ematen du. Bigarrenak, sare aukerak kudeatu eta sentsoreen konfigurazioa denbora errealean burutzen ditu. Inplementazio hau testuingurua hautemateko gai eta adierazgarria den aplikazio batekin egoera desberdinetan frogatu da. Lortutako emaitzek erakusten dute inplementazioa, eta ondorioz marko kontzeptuala ere, aproposa dela testuinguruaren informazioa erabiltzeko eta sentsoreen programazioa ezkutatzeko.[ES] Los dispositivos móviles disponibles en la actualidad facilitan el desarrollo de una nueva generación de aplicaciones móviles que son capaces de reaccionar al contexto. La computación sensible al contexto requiere datos del entorno que normalmente se obtienen por medio de sensores embebidos en dispositivos móviles o conectados a ellos a través de redes inalámbricas. Los desarrolladores de aplicaciones móviles se enfrentan a varios retos para crear aplicaciones sensibles al contexto. Entre estos retos destaca la necesidad de tratar la heterogeneidad de los sensores y de los dispositivos móviles. Con el fin de ayudar a los desarrolladores, esta tesis propone un marco conceptual para la abstracción multinivel y la virtualización de sensores, llamado Igerri. Su principal objetivo es facilitar el desarrollo de aplicaciones sensibles al contexto independientemente de los sensores específicos que se encuentren en el entorno. Para evitar la necesidad de manipular directamente los sensores físicos, se ha concebido una estructura multinivel de sensores virtuales y abstractos. Se han diseñado dos componentes software basados en el marco propuesto para comprobar la robustez de Igerri. El primero procesa la información de la estructura multinivel de sensores y genera información de contexto de alto nivel. El segundo es responsable de administrar, en tiempo real, las opciones de red y la configuración de los sensores. Esta implementación ha sido probada en diferentes escenarios usando una aplicación representativa y sensible al contexto. Los resultados obtenidos muestran que la implementación, y por tanto el marco conceptual que le da soporte, es adecuada para tratar la información de contexto y ocultar los problemas de programación de los sensores.Borja Gamecho held a PhD scholarship from the Research Staff Training Programme of the Basque Government from 2011 to 2014. This work also has been supported by the Department of Education, Universities and Research of the Basque Government under Grant IT395-10, by the Ministry of Economy and Competitiveness of the Spanish Government and by the European Regional Development Fund (project TIN2014-52665-C2-1)

Towards Posture and Gait Evaluation through Wearable-Based Biofeedback Technologies

In medicine and sport science, postural evaluation is an essential part of gait and posture correction. There are various instruments for quantifying the postural system’s efficiency and deter- mining postural stability which are considered state-of-the-art. However, such systems present many limitations related to accessibility, economic cost, size, intrusiveness, usability, and time-consuming set-up. To mitigate these limitations, this project aims to verify how wearable devices can be assem- bled and employed to provide feedback to human subjects for gait and posture improvement, which could be applied for sports performance or motor impairment rehabilitation (from neurodegenerative diseases, aging, or injuries). The project is divided into three parts: the first part provides experimen- tal protocols for studying action anticipation and related processes involved in controlling posture and gait based on state-of-the-art instrumentation. The second part provides a biofeedback strategy for these measures concerning the design of a low-cost wearable system. Finally, the third provides al- gorithmic processing of the biofeedback to customize the feedback based on performance conditions, including individual variability. Here, we provide a detailed experimental design that distinguishes significant postural indicators through a conjunct architecture that integrates state-of-the-art postural and gait control instrumentation and a data collection and analysis framework based on low-cost devices and freely accessible machine learning techniques. Preliminary results on 12 subjects showed that the proposed methodology accurately recognized the phases of the defined motor tasks (i.e., rotate, in position, APAs, drop, and recover) with overall F1-scores of 89.6% and 92.4%, respectively, concerning subject-independent and subject-dependent testing setups

Validation of mDurance, A Wearable Surface Electromyography System for Muscle Activity Assessment

The authors wish to thank all participants for their assistance and to Irene Cantarero-Villanueva Ph.D. and Paula Postigo-Martín, of the Department of Physiotherapy (University of Granada, Spain), for providing us with their laboratories and materials so that this study could be carried out.The mDurance® system is an innovative digital tool that combines wearable surface electromyography (sEMG), mobile computing and cloud analysis to streamline and automatize the assessment of muscle activity. The tool is particularly devised to support clinicians and sport professionals in their daily routines, as an assessment tool in the prevention, monitoring rehabilitation and training field. This study aimed at determining the validity of the mDurance system for measuring muscle activity by comparing sEMG output with a reference sEMG system, the Delsys® system. Fifteen participants were tested during isokinetic knee extensions at three different speeds (60, 180, and 300 deg/s), for two muscles (rectus femoris [RF] and vastus lateralis [VL]) and two different electrodes locations (proximal and distal placement). The maximum voluntary isometric contraction was carried out for the normalization of the signal, followed by dynamic isokinetic knee extensions for each speed. The sEMG output for both systems was obtained from the raw sEMG signal following mDurance's processing and filtering. Mean, median, first quartile, third quartile and 90th percentile was calculated from the sEMG amplitude signals for each system. The results show an almost perfect ICC relationship for the VL (ICC > 0.81) and substantial to almost perfect for the RF (ICC > 0.762) for all variables and speeds. The Bland-Altman plots revealed heteroscedasticity of error for mean, quartile 3 and 90th percentile (60 and 300 deg/s) for RF and at mean and 90th percentile for VL (300 deg/s). In conclusion, the results indicate that the mDurance® sEMG system is a valid tool to measure muscle activity during dynamic contractions over a range of speeds. This innovative system provides more time for clinicians (e.g., interpretation patients' pathologies) and sport trainers (e.g., advising athletes), thanks to automatic processing and filtering of the raw sEMG signal and generation of muscle activity reports in real-time

Smart Detection Of Arm Muscle Strength For Post Stroke Patient Therapy

Kelumpuhan otot merupakan fenomena yang sering terjadi di masyarakat khususnya pada pasien pasca stroke dan spinal cord injury (SCI). Kelumpuhan dapat terjadi karena adanya kerusakan atau stimulasi saraf ke otot baik yang disebabkan karena kerusakan saraf pusat maupun saraf perifer misalnya pada pasien pasca stroke dan spinal cord injury.  lektromiografi (EMG) adalah suatu teknik untuk mengevaluasi dan merekam sinyal aktivitas otot. Teknik ini mendeteksi potensial aksi dari sel-sel otot saat sel-sel berkontraksi dan relaksasi dengan menggunakan elektroda yang ditempel di atas jaringan otot. Pemeriksaan ini dapat membantu untuk membedakan antara masalah-masalah yang berasal dari otot itu sendiri atau dari gangguan syaraf. Sistem ini didesain untuk menyimpan dan menampilkan hasil monitoring nilai skala kekuatan otot pada smartphone android untuk multi-channel secara realtime. Sinyal dari instrumentasi elektromiograf Akan diolah pada Raspberry Pi melalui ADC kemudian dikirim ke database firebase melalui koneksi internet. Data yang telah dikirim kemudian ditampilkan pada smartphone android. Pada pengujian keseluruhan, sistem mampu mendeteksi nilai skala otot 0 sampai 5. Rata-rata waktu yang dibutuhkan untuk pengiriman data dari instrumentasi menuju aplikasi adalah 1 detik

PhysioVR: a novel mobile virtual reality framework for physiological computing

Virtual Reality (VR) is morphing into a ubiquitous technology by leveraging of smartphones and screenless cases in order to provide highly immersive experiences at a low price point. The result of this shift in paradigm is now known as mobile VR (mVR). Although mVR offers numerous advantages over conventional immersive VR methods, one of the biggest limitations is related with the interaction pathways available for the mVR experiences. Using physiological computing principles, we created the PhysioVR framework, an Open-Source software tool developed to facilitate the integration of physiological signals measured through wearable devices in mVR applications. PhysioVR includes heart rate (HR) signals from Android wearables, electroencephalography (EEG) signals from a low cost brain computer interface and electromyography (EMG) signals from a wireless armband. The physiological sensors are connected with a smartphone via Bluetooth and the PhysioVR facilitates the streaming of the data using UDP communication protocol, thus allowing a multicast transmission for a third party application such as the Unity3D game engine. Furthermore, the framework provides a bidirectional communication with the VR content allowing an external event triggering using a real-time control as well as data recording options. We developed a demo game project called EmoCat Rescue which encourage players to modulate HR levels in order to successfully complete the in-game mission. EmoCat Rescue is included in the PhysioVR project which can be freely downloaded. This framework simplifies the acquisition, streaming and recording of multiple physiological signals and parameters from wearable consumer devices providing a single and efficient interface to create novel physiologically-responsive mVR applications.info:eu-repo/semantics/publishedVersio

A wireless, minaturized multi-channel sEMG acquisition system for use in dynamic tasks

Nowadays, the detection of surface EMG (sEMG) signals is almost exclusively based on a single or a few electrode pairs. However, in the last two decades limitations of bipolar sEMG signals emerged. To increase the amount and reliability of information extracted from sEMG, linear electrode arrays and two-dimensional detection systems have been proposed. The aim of this work was the development of a wearable wireless, 32- channels sEMG acquisition system. The developed system performs the conditioning, sampling and wireless transmission of 32 monopolar sEMG channels and 3 auxiliary signals, sampled at 2.048ksps with 16 bit resolution. The system wirelessly transmits the acquired signals to either a mobile device (smartphone or tablet with Wi-Fi connectivity) or a personal computer for real time visualization and storage. The developed system has been tested in clinical and sport scenarios showing good performances in wearability and movement artefact robustness