A Motion Capturing and Energy Harvesting Hybridized Lower‐Limb System for Rehabilitation and Sports Applications

Abstract

Lower‐limb motion monitoring is highly desired in various application scenarios ranging from rehabilitation to sports training. However, there still lacks a cost‐effective, energy‐saving, and computational complexity‐reducing solution for this specific demand. Here, a motion capturing and energy harvesting hybridized lower‐limb (MC‐EH‐HL) system with 3D printing is demonstrated. It enables low‐frequency biomechanical energy harvesting with a sliding block‐rail piezoelectric generator (S‐PEG) and lower‐limb motion sensing with a ratchet‐based triboelectric nanogenerator (R‐TENG). A unique S‐PEG is proposed with particularly designed mechanical structures to convert lower‐limb 3D motion into 1D linear sliding on the rail. On the one hand, high output power is achieved with the S‐PEG working at a very low frequency, which realizes self‐sustainable systems for wireless sensing under the Internet of Things framework. On the other hand, the R‐TENG gives rise to digitalized triboelectric output, matching the rotation angles to the pulse numbers. Additional physical parameters can be estimated to enrich the sensory dimension. Accordingly, demonstrative rehabilitation, human‐machine interfacing in virtual reality, and sports monitoring are presented. This developed hybridized system exhibits an economic and energy‐efficient solution to support the need for lower‐limb motion tracking in various scenarios, paving the way for self‐sustainable multidimensional motion tracking systems in near future.

Abstract

A motion capturing and energy harvesting hybridized lower‐limb system is proposed for low‐frequency biomechanical energy harvesting and lower‐limb motion sensing. Combining with the Internet of Things framework, the hybridized system exhibits an economic and energy‐efficient solution to support the need for lower‐limb motion tracking in various applicable scenarios, paving the way for self‐sustainable multidimensional body motion tracking systems in near future.