Analysis of Eye Tracking of Physiotherapist during Walk Rehabilitation

The measurement of walking is important for evaluating the health of elderly people. This evaluation is performed by experts in gait assessment (such as doctors or physiotherapists), who vary in terms of skill. To guarantee evaluative quality, engineering of gait-measurement solutions is desired. This paper describes a method of quantifying tacit physiotherapist knowledge of walk rehabilitation by tracking and analysing their eyes. We constructed the eye-tracking system to extract the points of gaze of multiple physiotherapists. The result shows that proficient physiotherapists exhibit special eye movements, which we defined as ‘rhythmical’. We evaluated the proficiencies of all subjects based on their rhythmical-eye movement. It is clear that proficiency does not increase linearly with rhythmical-eye movement, but instead exhibits a staircase-like behaviour. Consequently, we elucidated that the ‘rhythmical-eye movement’ is one part of tacit knowledge of the proficient physiotherapists. And it is useful to establish the walking measurement closer to the proficient physiotherapists.

[1]  Tao Liu,et al.  Gait Analysis Using Wearable Sensors , 2012, Sensors.

[2]  Tomohiro Shirakawa,et al.  Gait analysis and machine learning classification on healthy subjects in normal walking , 2015, Int. J. Parallel Emergent Distributed Syst..

[3]  Guang-Zhong Yang,et al.  Validation of an ear-worn sensor for gait monitoring using a force-plate instrumented treadmill , 2012, Gait & Posture.

[4]  J. Dingwell,et al.  Kinematic variability and local dynamic stability of upper body motions when walking at different speeds. , 2006, Journal of biomechanics.

[5]  Hidetsugu Terada,et al.  Comparison between evaluation of the gravity center fluctuation and analysis of the motion of the leg in walking rehabilitation , 2016, 2016 IEEE International Conference on Industrial Technology (ICIT).

[6]  Denise M. Peters,et al.  Assessing the Reliability and Validity of a Shorter Walk Test Compared With the 10-Meter Walk Test for Measurements of Gait Speed in Healthy, Older Adults , 2013, Journal of geriatric physical therapy.

[7]  K. Rayner.  Eye movements in reading and information processing: 20 years of research. , 1998, Psychological bulletin.

[8]  Gu-Min Jeong,et al.  Stride Counting in Human Walking and Walking Distance Estimation Using Insole Sensors , 2016, Sensors.

[9]  I. Rosenberg,et al.  Sarcopenia: origins and clinical relevance. , 1997, The Journal of nutrition.

[10]  Steven H Collins,et al.  Dynamic arm swinging in human walking , 2009, Proceedings of the Royal Society B: Biological Sciences.

[11]  Atsushi Yamashita,et al.  Skill Abstraction of Physical Therapists in Hemiplegia Patient Rehabilitation Using a Walking Assist Robot , 2019, Int. J. Autom. Technol..

[12]  Hidetsugu Terada,et al.  Evaluation method of the gait motion based on self-organizing map using the gravity center fluctuation on the sole , 2017, Int. J. Autom. Comput..

[13]  D Hamerman,et al.  Toward an Understanding of Frailty , 1999, Annals of Internal Medicine.

[14]  G. Smidt,et al.  Measurement of hip-joint motion during walking. Evaluation of an electrogoniometric method. , 1969, The Journal of bone and joint surgery. American volume.

[15]  Lucas Kovar,et al.  Splicing Upper‐Body Actions with Locomotion , 2006, Comput. Graph. Forum.

[16]  Tomohiro Shirakawa,et al.  Gait analysis and machine learning classification on healthy subjects in normal walking , 2015 .

[17]  Lucas R Nascimento,et al.  Different instructions during the ten-meter walking test determined significant increases in maximum gait speed in individuals with chronic hemiparesis. , 2012, Revista brasileira de fisioterapia (Sao Carlos (Sao Paulo, Brazil)).

[18]  Ran Gilad-Bachrach,et al.  Full body gait analysis with Kinect , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.