Intelligent assistive system using real-time action recognition for stroke survivors

Emilie M.D. Jean-Baptiste; Roozbeh Nabiei; Manish Parekh; Evangelia Fringi; Bogna Drozdowska; Chris Baber; Peter Jancovic; Pia Rotshein; Martin Russell

doi:10.1109/ICHI.2014.13

Intelligent assistive system using real-time action recognition for stroke survivors

Emilie M.D. Jean-Baptiste, Roozbeh Nabiei, Manish Parekh, Evangelia Fringi, Bogna Drozdowska, Chris Baber, Peter Jancovic, Pia Rotshein, Martin Russell

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	39-44
Number of pages	6
ISBN (Electronic)	9781479957019
DOIs	https://doi.org/10.1109/ICHI.2014.13
State	Published - 2 Mar 2014
Externally published	Yes
Event	2014 2nd IEEE International Conference on Healthcare Informatics, ICHI 2014 - Verona, Italy Duration: 15 Sep 2014 → 17 Sep 2014

Publication series

Name	Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014

Conference

Conference	2014 2nd IEEE International Conference on Healthcare Informatics, ICHI 2014
Country/Territory	Italy
City	Verona
Period	15/09/14 → 17/09/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

Action Recognition
HMM
MDP
Rehabilitation System
Task Model

ASJC Scopus subject areas

Health Informatics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICHI.2014.13

Cite this

Jean-Baptiste, E. M. D., Nabiei, R., Parekh, M., Fringi, E., Drozdowska, B., Baber, C., Jancovic, P., Rotshein, P., & Russell, M. (2014). Intelligent assistive system using real-time action recognition for stroke survivors. In Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014 (pp. 39-44). Article 7052468 (Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICHI.2014.13

Jean-Baptiste, Emilie M.D. ; Nabiei, Roozbeh ; Parekh, Manish et al. / Intelligent assistive system using real-time action recognition for stroke survivors. Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 39-44 (Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014).

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title = "Intelligent assistive system using real-time action recognition for stroke survivors",

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 = "Action Recognition, HMM, MDP, Rehabilitation System, Task Model",

author = "Jean-Baptiste, {Emilie M.D.} and Roozbeh Nabiei and Manish Parekh and Evangelia Fringi and Bogna Drozdowska and Chris Baber and Peter Jancovic and Pia Rotshein and Martin Russell",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 2nd IEEE International Conference on Healthcare Informatics, ICHI 2014 ; Conference date: 15-09-2014 Through 17-09-2014",

year = "2014",

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doi = "10.1109/ICHI.2014.13",

language = "English",

series = "Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014",

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Jean-Baptiste, EMD, Nabiei, R, Parekh, M, Fringi, E, Drozdowska, B, Baber, C, Jancovic, P, Rotshein, P & Russell, M 2014, Intelligent assistive system using real-time action recognition for stroke survivors. in Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014., 7052468, Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014, Institute of Electrical and Electronics Engineers Inc., pp. 39-44, 2014 2nd IEEE International Conference on Healthcare Informatics, ICHI 2014, Verona, Italy, 15/09/14. https://doi.org/10.1109/ICHI.2014.13

Intelligent assistive system using real-time action recognition for stroke survivors. / Jean-Baptiste, Emilie M.D.; Nabiei, Roozbeh; Parekh, Manish et al.
Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 39-44 7052468 (Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Intelligent assistive system using real-time action recognition for stroke survivors

AU - Jean-Baptiste, Emilie M.D.

AU - Nabiei, Roozbeh

AU - Parekh, Manish

AU - Fringi, Evangelia

AU - Drozdowska, Bogna

AU - Baber, Chris

AU - Jancovic, Peter

AU - Rotshein, Pia

AU - Russell, Martin

PY - 2014/3/2

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N2 - 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.

AB - 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.

KW - Action Recognition

KW - HMM

KW - MDP

KW - Rehabilitation System

KW - Task Model

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BT - Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Jean-Baptiste EMD, Nabiei R, Parekh M, Fringi E, Drozdowska B, Baber C et al. Intelligent assistive system using real-time action recognition for stroke survivors. In Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 39-44. 7052468. (Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014). doi: 10.1109/ICHI.2014.13

Intelligent assistive system using real-time action recognition for stroke survivors

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this