TY - GEN
T1 - Med fit
T2 - 2nd International Workshop on Multimedia for Personal Health and Health Care, MMHealth 2017
AU - Kuklyte, Jogile
AU - Gualano, Leonardo
AU - Prabhu, Ghanashyama
AU - Venkataraman, Kaushik
AU - Walsh, Deirdre
AU - Woods, Catherine
AU - Moran, Kieran
AU - O'Connor, Noel E.
N1 - Publisher Copyright:
© 2017 Association for Computing Machinery.
PY - 2017/10/23
Y1 - 2017/10/23
N2 - The third phase of the recovery from cardiovascular disease (CVD) is an exercise-based rehabilitation programme. However, adherence to an exercise regime is typically not maintained by the patient for a variety of reasons such as lack of time, financial constraints, etc. In order to facilitate patients to perform their exercises from the comfort of their home and at their own convenience, we have developed a mobile application, termed MedFit. It provides access to a tailored suite of exercises along with easy to understand guidance from audio and video instructions. Two types of wearable sensors are utilized to provide motivational feedback. Fitbit, a commercially available activity and fitness tracker, is used to provide in-depth feedback for self-monitoring over longer periods of time (e.g. day, week, month), whereas the Shimmer wireless sensing platform provides the data for near real-time feedback on the quality of the exercises performed. MedFit is a simple and intuitive mobile application designed to provide the motivation and tools for patients to help ensure faster recovery from the trauma caused by CVD. In this paper we describe features available in the MedFit application and the overall motivation behind the project.
AB - The third phase of the recovery from cardiovascular disease (CVD) is an exercise-based rehabilitation programme. However, adherence to an exercise regime is typically not maintained by the patient for a variety of reasons such as lack of time, financial constraints, etc. In order to facilitate patients to perform their exercises from the comfort of their home and at their own convenience, we have developed a mobile application, termed MedFit. It provides access to a tailored suite of exercises along with easy to understand guidance from audio and video instructions. Two types of wearable sensors are utilized to provide motivational feedback. Fitbit, a commercially available activity and fitness tracker, is used to provide in-depth feedback for self-monitoring over longer periods of time (e.g. day, week, month), whereas the Shimmer wireless sensing platform provides the data for near real-time feedback on the quality of the exercises performed. MedFit is a simple and intuitive mobile application designed to provide the motivation and tools for patients to help ensure faster recovery from the trauma caused by CVD. In this paper we describe features available in the MedFit application and the overall motivation behind the project.
KW - Activity Recognition
KW - Cardiovascular disease
KW - Mobile Application
KW - Repetition Counting
KW - Wearable Sensors
UR - http://www.scopus.com/inward/record.url?scp=85034823532&partnerID=8YFLogxK
U2 - 10.1145/3132635.3132651
DO - 10.1145/3132635.3132651
M3 - Conference contribution
AN - SCOPUS:85034823532
T3 - MMHealth 2017 - Proceedings of the 2nd International Workshop on Multimedia for Personal Health and Health Care, co-located with MM 2017
SP - 93
EP - 96
BT - MMHealth 2017 - Proceedings of the 2nd International Workshop on Multimedia for Personal Health and Health Care, co-located with MM 2017
PB - Association for Computing Machinery, Inc
Y2 - 23 October 2017
ER -
