Wearable robotic exoskeletons (WREs) have been developed from orthoses as assistive devices for gait reconstruction in patients with spinal cord injury. They can solve some problems encountered with orthoses, such as difficulty in independent walking and standing up and high energy consumption during walking. The Wearable Power-Assist Locomotor (WPAL), a WRE, was developed based on a knee–ankle–foot orthosis with a single medial hip joint. The WPAL has been updated seven times during the period from the beginning of its development, in 2005, to 2020. The latest version, launched as a commercialized model in 2016, is available for medical facilities. In this retrospective study, which included updated results from previous reports, all data were extracted from development research records from July 2007 to December 2020. The records were as follows: patient characteristics [the number of participants, injury level, and the American Spinal Injury Association Impairment Scale (AIS) score], the total number of WPAL trials when aggregating the cases with all the versions or only the latest version of the WPAL, and maximum walking performance (functional ambulation category [FAC], distance, and time of continuous walking). Thirty-one patients participated in the development research. The levels of spinal cord injury were cervical (C5–C8), upper thoracic (T3–T6), lower thoracic (T7–T12), and lumbar (L1) in 10, 5, 15, and 1 of the patients, respectively. The numbers of patients with AIS scores of A, B, C, and D were 20, 7, 4, and 0, respectively. The total number of WPAL trials was 1,785, of which 1,009 were used the latest version of the WPAL. Twenty of the patients achieved an FAC score of 4 after an average of 9 (median 8, range 2–22) WPAL trials. The continuous walking distance and time improved with the WPAL were compared to the orthosis. We confirmed that the WPAL improves walking independence in people with a wide range of spinal cord injuries, such as cervical spinal cord injuries. Further refinement of the WPAL will enable its long-term use at home.
All Science Journal Classification (ASJC) codes
- Biomedical Engineering
- Artificial Intelligence