Abstract
For a successful rehabilitation after cardiac surgery, it is crucial to have a carefully personalized, structured, and supervised physiotherapy program. Due to erroneous or unsupervised physiotherapy, nearly 50% of surgeries fail. Researchers have tried to leverage advances in wearable sensors and motion tracking to build affordable, automated, and customizable rehabilitation systems that help both therapists and patients during physiotherapy sessions. In this paper, we present a patient-centered cardiac surgery rehabilitation system (CSRS) for the personalization of the patient's physiotherapy for the early post-operative period. The system has been designed to interconnect different acquisition sensors and to be distributed on different stations in order to be able to continuously monitor the patient's vital signs and evaluate her/his cognitive and motor abilities in real time.
Original language | English |
---|---|
Title of host publication | Proceedings - 13th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2017 |
Editors | Albert Dipanda, Richard Chbeir, Neeta Nain, Kokou Yetongnon, Luigi Gallo |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 83-90 |
Number of pages | 8 |
Volume | 2018-January |
ISBN (Electronic) | 9781538642832 |
DOIs | |
Publication status | Published - Apr 9 2018 |
Event | 13th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2017 - Jaipur, India Duration: Dec 4 2017 → Dec 7 2017 |
Conference
Conference | 13th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2017 |
---|---|
Country/Territory | India |
City | Jaipur |
Period | 12/4/17 → 12/7/17 |
Keywords
- Cardiac Surgery Rehabilitation System
- Cognitive and physical abilities monitoring
- Patient-centered environment
- Personalized Rehabilitation Sessions
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Signal Processing