Transportable and scalable system for activities and exercises recognition in real-time
- Resource Type
- Conference
- Authors
- Chapron, Kevin; Bouchard, Kevin; Duchesne, Elise; Gaboury, Sebastien
- Source
- 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), 2017 IEEE. :1-7 Aug, 2017
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Sensors
Batteries
Protocols
Microsoft Windows
Wireless fidelity
Muscles
Wrist
- Language
Patients concerned with neuromuscular disorders are usually given a program of multiple physical exercises to do. These exercises must be recognized by devices to ensure the therapist that the patient did it well. To this end, we developed a specific method allowing the recognition of two types of activities on different window sizes. The method consists of two devices communicating over Wi-Fi, to use both wearable components and powerful embedded computer. Data is collected during fixed windows by the first device. Then features are calculated on the retrieved data for the recognition algorithm. Participants took part in an experiment based on four physical exercises and six daily activities. The method induced good results.