FootStriker: An EMS-based Foot Strike Assistant for Running

Mahmoud Hassan; Florian Daiber; Frederik Wiehr; Felix Kosmalla; Antonio Krüger

In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Vol. 1, No. 1, Pages 2:1-2:18, ACM, New York, NY, USA, 3/2017.


In running, knee-related injuries are very common. The main cause are high impact forces when striking the ground with the heel first. Mid- or forefoot running is generally known to reduce impact loads and to be a more efficient running style. In this paper, we introduce a wearable running assistant, consisting of an electrical muscle stimulation (EMS) device and an insole with force sensing resistors. It detects heel striking and actuates the calf muscles during the flight phase to control the foot angle before landing. We conducted a user study, in which we compared the classical coaching approach using slow motion video analysis as a terminal feedback to our proposed real-time EMS feedback. The results show that EMS actuation significantly outperforms traditional coaching, i.e., a decreased average heel striking rate, when using the system. As an implication, EMS feedback can generally be beneficial for the motor learning of complex, repetitive movements.


Weitere Links

Footstriker-CameraReady-ACM.pdf (pdf, 5 MB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence