Title :
Intelligent Assistive System Using Real-Time Action Recognition for Stroke Survivors
Author :
Jean-Baptiste, Emilie M. D. ; Nabiei, Roozbeh ; Parekh, Manish ; Fringi, Evangelia ; Drozdowska, Bogna ; Baber, Chris ; Jancovic, Peter ; Rotshein, Pia ; Russell, Martin
Author_Institution :
Sch. of Electron. Electr. & Comput. Eng., Univ. of Birmingham, Birmingham, UK
Abstract :
Cog Watch is an EU project developing technologies for cognitive rehabilitation of stroke patients. The Cog Watch prototype is an automatic system to re-train patients with Apraxia or Action Disorganization Syndrome (AADS) to complete activities of daily living (ADLs). This paper describes the approach to automatic planning based on a Markov Decision Process, and real-time action recognition (AR) based on instrumented objects using Hidden Markov Models. The experimental results demonstrate the ability of a psychologically plausible planning system integrated in a Task Model (TM) to improve task performance via user simulation, and the viability of the approach to AR.
Keywords :
cognition; decision theory; hidden Markov models; medical computing; patient rehabilitation; AADS; ADLs; AR; Cog Watch; Markov decision process; TM; action disorganization syndrome; activities of daily living; apraxia; automatic planning; cognitive rehabilitation; hidden Markov models; intelligent assistive system; patient retraining; real-time action recognition; stroke survivors; task model; task performance improvement; user simulation; Artificial intelligence; Dairy products; Detectors; Hidden Markov models; Psychology; Sugar; Action Recognition; HMM; MDP; Rehabilitation System; Task Model;
Conference_Titel :
Healthcare Informatics (ICHI), 2014 IEEE International Conference on
DOI :
10.1109/ICHI.2014.13
