AI in evaluating ambulation of stroke patients: severity classification with video and functional ambulation category scale

Author:

Kim Jeong-Hyun1ORCID,Hong Hyeon1ORCID,Lee Kyuwon1ORCID,Jeong Yeji1,Ryu Hokyoung2,Kim Hyundo3,Jang Seong-Ho4,Park Hyeng-Kyu5,Han Jae-Young5,Park Hye Jung6,Bae Hasuk7,Oh Byung-Mo8,Kim Won-Seok9,Lee Sang Yoon10,Lee Shi-Uk111ORCID

Affiliation:

1. Department of Rehabilitation Medicine, Seoul Metropolitan Government Boramae Medical Center, Seoul, South Korea

2. Department of Graduate School of Technology and Innovation Management, Hanyang University, Seoul, South Korea

3. Department of Intelligence Computing, Hanyang University, Seoul, South Korea

4. Department of Rehabilitation Medicine, Hanyang University, Guri Hospital, Gyeonggi-do, South Korea

5. Department of Physical & Rehabilitation Medicine, Regional Cardiocerebrovascular Center, Center for Aging and Geriatrics, Chonnam National University Medical School & Hospital, Gwangju, South Korea

6. Department of Rehabilitation Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea

7. Department of Rehabilitation Medicine, Ewha Woman’s University, Seoul, South Korea

8. Department of Rehabilitation, Seoul National University Hospital, Seoul, South Korea

9. Department of Rehabilitation Medicine, Seoul National University College of Medicine, Seoul, South Korea

10. Department of Rehabilitation Medicine, Seoul National University College of Medicine, SMG-SNU Boramae Medical Center, Seoul, South Korea

11. Department of Physical Medicine & Rehabilitation, College of Medicine, Seoul National University, Seoul, South Korea

Funder

Korea Medical Device Development

the Korean government

he Ministry of Science

the Ministry of Trade

Industry and Energy

Ministry of Health & Welfare, the Ministry of Food and Drug Safety

Publisher

Informa UK Limited

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