A proposed pervasive smartphone application for personalised gait rehabilitation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Falls due to compromised mobility issues in older adults (e.g., those with Parkinson's Disease, PD) indicate the necessity for accurate assessment and methods for targeted rehabilitation. The latter often focuses on gait retraining with an auditory cue but often requires a baseline gait assessment. Inertial measurement units (IMUs) have emerged as a more readily deployable gait assessment method compared to traditional instrumented walkways. IMUs are a near ubiquitous technology as they are often found in smartphones. The pilot work presented here details the development and validation of a novel smartphone application using embedded IMUs for near real-time gait assessment. Additionally, coupled with the added functionality of a smartphone, personalized metronome cueing is delivered to assess its functionality for gait retraining. A sample of healthy adults were recruited with gait characteristics verified against a reference standard. Next, the cueing approach showed an average increase in pace of 10.6% among participants, broadly aligning with the intended goal of 10.0%. The proposed smartphone approach demonstrates robustness with strong correlations (≥0.858) for step time, stride time, stance time, swing time, and cadence, with equally strong intraclass correlation coefficients (≥0.911) pre- and post-cueing. The pervasive smartphone approach for gait assessment with a metronome cue for gait retraining shows the potential to deliver a scalable and personalized rehabilitation which could improve mobility and reduce falls. The next stage of work will focus on (i) a larger, diverse cohort of people with PD and (ii) exploration of other personalized cueing to enhance continued adherence.
Original languageEnglish
Title of host publication2023 IEEE-EMBS International Conference on Body Sensor Networks - Sensors and Systems for Digital Health (BSN)
Place of PublicationPiscataway, US
Number of pages6
Publication statusAccepted/In press - 15 Jul 2023
EventIEEE-EMBS International Conference on Body Sensor Networks
: Sensor and Systems for Digital Health (IEEE BSN 2023)
- MIT Media Lab, Boston, United States
Duration: 9 Oct 202311 Oct 2023


ConferenceIEEE-EMBS International Conference on Body Sensor Networks
Abbreviated titleIEEE BSN 2023
Country/TerritoryUnited States
Internet address

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