TY - CHAP
T1 - Multi-Purpose Long-Term Gait Analysis Platform
AU - Codina, Marc
AU - Castells-Rufas, David
AU - Carrabina, Jordi
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper introduces an innovative health platform that seamlessly combines wearable devices, data acquisition from sensors, data analysis, and telehealth services to establish an all-encompassing and interconnected healthcare environment. The primary goal of this platform is to provide an efficient, preventive and user-friendly solution to profit the raw data on health constants and physical activity emanating from everyday more popular wearable devices for its meaningful clinical interpretation. This is achieved by transforming the real-Time data into various health parameters and indices oriented to specific clinical purposes. Initially, selected applications are balance and stability as a long-Term measure of equilibrium, surgery recovery (for those that affect gait e.g., hit) and gait detection and prevention. All of them are of special interest to ensure the personal autonomy of older individuals. In order to ensure efficient connectivity and the proficient management of health data, the platform adopts a cutting-edge device-edge-cloud IoT architecture connected to mobile devices (mHealth). This architecture allows for the vigilant monitoring of patients, leading to the generation of insightful health reports. The platform's data analysis capabilities assume a pivotal role in aiding medical diagnostics by detecting discernible patterns, trends, and irregularities that may signify underlying health concerns with the help or artificial intelligence. This functionality empowers healthcare professionals to deliver more precise diagnoses and personalized treatment plans. What sets this platform apart is its comprehensive nature, addressing the limitations inherent in existing systems, particularly in the realm of medical applications and the specific needs of the elderly. It establishes a more holistic and integrated approach to personalized care.
AB - This paper introduces an innovative health platform that seamlessly combines wearable devices, data acquisition from sensors, data analysis, and telehealth services to establish an all-encompassing and interconnected healthcare environment. The primary goal of this platform is to provide an efficient, preventive and user-friendly solution to profit the raw data on health constants and physical activity emanating from everyday more popular wearable devices for its meaningful clinical interpretation. This is achieved by transforming the real-Time data into various health parameters and indices oriented to specific clinical purposes. Initially, selected applications are balance and stability as a long-Term measure of equilibrium, surgery recovery (for those that affect gait e.g., hit) and gait detection and prevention. All of them are of special interest to ensure the personal autonomy of older individuals. In order to ensure efficient connectivity and the proficient management of health data, the platform adopts a cutting-edge device-edge-cloud IoT architecture connected to mobile devices (mHealth). This architecture allows for the vigilant monitoring of patients, leading to the generation of insightful health reports. The platform's data analysis capabilities assume a pivotal role in aiding medical diagnostics by detecting discernible patterns, trends, and irregularities that may signify underlying health concerns with the help or artificial intelligence. This functionality empowers healthcare professionals to deliver more precise diagnoses and personalized treatment plans. What sets this platform apart is its comprehensive nature, addressing the limitations inherent in existing systems, particularly in the realm of medical applications and the specific needs of the elderly. It establishes a more holistic and integrated approach to personalized care.
KW - data analysis
KW - health platform
KW - internet of medical things
KW - tele-health services
KW - wearable devices
UR - http://www.scopus.com/inward/record.url?scp=85190702885&partnerID=8YFLogxK
U2 - 10.1109/ICTE58739.2023.10488590
DO - 10.1109/ICTE58739.2023.10488590
M3 - Chapter
AN - SCOPUS:85190702885
T3 - 2023 IEEE International Conference on Technology and Entrepreneurship, ICTE 2023
SP - 98
EP - 103
BT - 2023 IEEE International Conference on Technology and Entrepreneurship, ICTE 2023
A2 - Pundziene, Asta
A2 - Pundziene, Asta
A2 - Gadeikiene, Agne
A2 - Bez, Sea Matilda
A2 - Dagiliene, Lina
A2 - Daim, Tugrul
A2 - Gerulaitiene, Neringa
A2 - Koushik, Sudeendra
A2 - Mathieu, Christopher
A2 - Park, Taeho
A2 - Petraite, Monika
A2 - Prior, Diego
A2 - Quan, Xiaohong
A2 - Savaneviciene, Asta
A2 - Varri, Alpo
A2 - Vilkas, Mantas
PB - Institute of Electrical and Electronics Engineers Inc.
ER -