Uppsats

Cadence and Stride Length Measurement Using a Foot-Mounted IMU

Kandidat-uppsats

Chalmers tekniska högskola / Institutionen för data och informationsteknik

Publicerad: 2026

Språk: Engelska

Sammanfattning

The purpose of this project was to develop a prototype for measuring cadence (stepfrequency) and stride length directly from the foot, enabling the collected data tobe visualized and presented to the user in a mobile application. These metricsare relevant because they can provide runners with insight into their running technique and help users identify patterns that may contribute to more efficient training.Two different prototypes were developed and evaluated. The first prototype wasa lace-mounted design using an Inertial Measurement Unit (IMU)-based step detection algorithm. The second prototype was a sole-based prototype, where the IMUwas placed in a cutout on the insole and pressure sensors were used for step detection. For stride length estimation, both systems employed an Extended KalmanFilter (EKF) on the IMU data. The systems communicated with a mobile application via Bluetooth Low Energy (BLE), enabling the collected data to be presentedto the user in a graphical interface.The results showed that both designs performed similarly in terms of step detection, achieving more accurate measurements during running and jogging comparedto walking. However, regarding stride length estimation, the sole-based prototypeoutperformed the lace-mounted prototype across all tests, achieving Mean AbsoluteRelative Error (MARE) values between 5.57% and 15.15%, compared to 27.57% to35.32%.Overall, the results indicated that the sole-based prototype provides more reliableperformance than the lace-mounted prototype. However, this came with a trade-offbetween usability and performance, which was a recurring challenge throughout theproject. The developed prototypes demonstrated the potential of foot-mounted sensing as an alternative to smartwatch-based measurements and highlighted promisingopportunities for future development in running analysis applications.

Information

Lärosäte / institution
Chalmers tekniska högskola / Institutionen för data och informationsteknik
Publiceringsdatum
2026
Uppsatstyp
Kandidat-uppsats
Språk
Engelska