Development of an algorithm to predict comfort of wheelchair fit based on clinical measures

Keisuke Kon, Yasuyuki Hayakawa, Shingo Shimizu, Toshiya Nosaka, Takeshi Tsuruga, Hiroyuki Matsubara, Tomohiro Nomura, Shin Murahara, Hirokazu Haruna, Takumi Ino, Jun Inagaki, Toshiki Kobayashi

Research output: Journal article publicationJournal articleAcademic researchpeer-review


[Purpose] The purpose of this study was to develop an algorithm to predict the comfort of a subject seated in a wheelchair, based on common clinical measurements and without depending on verbal communication. [Subjects] Twenty healthy males (mean age: 21.5 ± 2 years; height: 171 ± 4.3 cm; weight: 56 ± 12.3 kg) participated in this study. [Methods] Each experimental session lasted for 60 min. The clinical measurements were obtained under 4 conditions (good posture, with and without a cushion; bad posture, with and without a cushion). Multiple regression analysis was performed to determine the relationship between a visual analogue scale and exercise physiology parameters (respiratory and metabolism), autonomic nervous parameters (heart rate, blood pressure, and salivary amylase level), and 3D-coordinate posture parameters (good or bad posture). [Results] For the equation (algorithm) to predict the visual analogue scale score, the adjusted multiple correlation coefficient was 0.72, the residual standard deviation was 1.2, and the prediction error was 12%. [Conclusion] The algorithm developed in this study could predict the comfort of healthy male seated in a wheelchair with 72% accuracy.

Original languageEnglish
Pages (from-to)2813-2816
Number of pages4
JournalJournal of Physical Therapy Science
Issue number9
Publication statusPublished - 30 Sept 2015
Externally publishedYes


  • Multivariate analysis
  • Posture maintenance
  • Wheelchair seating

ASJC Scopus subject areas

  • Physical Therapy, Sports Therapy and Rehabilitation


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