Lightweight markerless identification of temporal gait outcomes with BlazePose

Fraser Young, Conor Wall, Lisa Graham, Samuel Stuart, Rosie Morris, Alan Godfrey*

*Corresponding author for this work

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


Traditionally, gait analysis is carried out in controlled settings, conducted by a trained professional which can limit reproducibility, validity, and inter-rater reliability. Recently, wearable inertial measuring units (IMUs) have been used to objectively measure gait characteristics. However, the need for manual attachment as well as data extraction and analysis, can create practical limitations, especially within low-resource environments. Lightweight artificial intelligence (AI) models for scalable and direct use on smartphones may also offer a more practical and routine gait assessment. Here, the proposed approach in this paper implements BlazePose, a lightweight pose estimation framework able to estimate 3D anatomical locations from a smartphone-based video stream. Anatomical locations inform a gait feature extraction layer to estimate step, stride, contact and swing times. The proposed approach was validated against a reference (proxy) standard (MobilityLab, APDM), performing robustly (ICC2,1 = 0.859-0.99, p=0.756-0.984). The proposed approach eliminates the need for specific hardware such as wearables, making it more cost-effective, accessible and scalable for gait assessment in low-resource settings.
Original languageEnglish
Title of host publication2023 IEEE 19th International Conference on Body Sensor Networks (BSN)
Place of PublicationPiscataway, US
ISBN (Electronic)9798350338416
ISBN (Print)9798350311983
Publication statusPublished - 9 Oct 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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