RadarFoot: Fine-grain ground surface context awareness for smart shoes

Don Samitha Elvitigala, Yunfan Wang, Yongquan Hu, Aaron J. Quigley

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


Everyday, billions of people use footwear for walking, running, or exercise. Of emerging interest are "smart footwear", which help users track gait, count steps or even analyse performance. However, such nascent footwear lack fine-grain ground surface context awareness, which could allow them to adapt to the conditions and create usable functions and experiences. Hence, this research aims to recognize the walking surface using a radar sensor embedded in a shoe, enabling ground context-awareness. Using data collected from 23 participants from an in-the-wild setting, we developed several classification models. We show that our model can detect five common terrain types with an accuracy of 80.0% and further ten terrain types with an accuracy of 66.3%, while moving. Importantly, it can detect the gait motion types such as 'walking', 'stepping up', 'stepping down', 'still', with an accuracy of 90%. Finally, we present potential use cases and insights for future work based on such ground-aware smart shoes.

Original languageEnglish
Title of host publicationProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology
EditorsJurgen Steimle, Nathalie Henry Riche
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages13
ISBN (Electronic)9798400701320
Publication statusPublished - 2023
EventACM Symposium on User Interface Software and Technology 2023 - San Francisco, United States of America
Duration: 29 Oct 20231 Nov 2023
Conference number: 36th
https://dl.acm.org/doi/proceedings/10.1145/3586183 (Proceedings)
https://uist.acm.org/2023/ (Website)


ConferenceACM Symposium on User Interface Software and Technology 2023
Abbreviated titleUIST 2023
Country/TerritoryUnited States of America
CitySan Francisco
Internet address


  • Context Awareness
  • Machine Learning
  • mmWave Radar
  • Radar
  • Smart Footwear
  • Smart shoes
  • Wearables

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