Attitudes towards a sensor-feedback technology in gait rehabilitation of patients after stroke
Creators: name: Nieboer, Marianne
name: Jie, Li-Juan
name: Willemse, Lydia
name: Peek, Sebastiaan
name: Braun, Susy
name: Wouters, Eveline
Publisher: name: Taylor & Francis
Year: 2021
Subjects: subject: Space Science
subject: Microbiology
subject: FOS: Biological sciences
classificationCode: 59999
subject: Environmental Sciences not elsewhere classified
classificationCode: 69999
subject: Biological Sciences not elsewhere classified
subject: Science Policy
classificationCode: 111714
subject: Mental Health
subject: Computational Biology

description: Intensive gait training is important for effective rehabilitation of people after stroke. “Stappy” is a sensor-feedback system that provides real-time feedback on the persons gait pattern/performance during training. The main aim of this study was to assess attitudes towards “Stappy” in people after stroke to practise walking performance independently at home. Demographics were collected. Frequency of practice with “Stappy” was monitored through the system. Participants used “Stappy” at home for two weeks. Semi-structured interviews were conducted to explore patient experiences with “Stappy” afterwards. Interviews were analysed using thematic analysis. Seventeen people after stroke (13 males, mean age 65, 17 to 172 months after stroke) were interviewed. There was a large variability (ranging from 0 to 14 days) in frequency of use over the two-week period. Although, thirty-eight percent were non-users, participants seemed satisfied about the option of feedback of the system on people’s gait pattern. Moderate to frequent users reported the ability to integrate “Stappy” into daily walking and the presence of support by the social environment as important factors for use. In a sub sample of stroke patients the ability to receive real-time feedback during practice about walking performance at home was viewed positively. Six participants did not or hardly used the sensor-feedback technology, even though they were positive about potential benefits. This implies that mHealth is not eligible for all individuals. To improve adherence various considerations were derived from this study, that may further optimise the frequency and personalise the use of the technology.IMPLICATIONS FOR REHABILITATIONThe frequency of use of a sensor-feedback technology in gait rehabilitation varied a lot in a cross-sectional sample of people after stroke.Patients after stroke seemed to have a positive attitude towards a sensor-feedback technology to support unsupervised practice of walking. However, this was unrelated to whether they had used or had not used the technology.Moderate and frequent users of the sensor-feedback technology reported the ability to integrate sensor-feedback technology in daily life and social support as important factors for use.For clinical practice in gait rehabilitation it is important to screen which patients are capable to use and may benefit from a technology as the one used in this study. The frequency of use of a sensor-feedback technology in gait rehabilitation varied a lot in a cross-sectional sample of people after stroke. Patients after stroke seemed to have a positive attitude towards a sensor-feedback technology to support unsupervised practice of walking. However, this was unrelated to whether they had used or had not used the technology. Moderate and frequent users of the sensor-feedback technology reported the ability to integrate sensor-feedback technology in daily life and social support as important factors for use. For clinical practice in gait rehabilitation it is important to screen which patients are capable to use and may benefit from a technology as the one used in this study.