Gait analysis is an established research area for many medical and healthcare applications. These applications range from evaluating the efficacy of orthoses, prosthetics, surgical procedures, or rehabilitation treatment (e.g., for knee surgery or stroke recovery), through aiding diagnosis and assessment of neuropathies, to monitoring gait degradation, assessing fall risks, and preventing falls for the elderly.
The quality and validity of these gait analysis applications are dependent on the measuring instruments used. In current clinical settings, gait analysis is usually performed by subjective and qualitative approaches, such as human observation and patient self-reporting. In this way, the main quantitative measures that can be derived are cadence, gait speed, and distance covered. These are oversimplified measures for assessing human gait – a complex mechanism governed by the neuromuscular system. Although some severe gait disorders can be observed by human eyes, without quantitative measures, subtle changes can go unnoticed. Furthermore, these approaches typically involve significant inter- and intraobserver variabilities, thus affecting disease staging, severity assessment, and subsequent treatment planning.