STEAR: Robust Step Counting from Earables

Jay Prakash, Zhijian Yang, Yu-Lin Wei, Romit Roy Choudhury

Abstract: This paper shows that inertial measurement units (IMUs) inside earphones offer a clear advantage in counting the number of steps a user has walked. While step-count has been extensively studied in the mobile computing community, there is wide consensus that false positives are common. The main reason for false positives is due to limb and device motions producing the same periodic bounce as the human walk. However, when IMUs are at the ear, we find that many of the lower-body motions are naturally "filtered out", i.e., these noisy motions do not propagate all the way up to the ear. Hence, the earphone IMU detects a bounce produced only from walking. While head movements can still pollute this bouncing signal, we develop methods to alleviate the problem. Results show 95% step-count accuracy even in the most difficult test case -- very slow walk -- where smartphone and fitbit-like systems falter. Importantly, our system STEAR is robust to changes in walking patterns and scales well across different users. Additionally, we demonstrate how STEAR also bring opportunities for effective jump analysis, often important for exercises and injury-related rehabilitation.