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As described in Chapter 2, many physical or mental diseases or abnormalities directly or indirectly affect human gait. Stroke, Parkinson's, and leg amputation readily come to mind. Thus, gait analysis can be used to monitor both the cause and the symptoms of a wide range of such abnormalities. The state of gait can be measured using a number of sensing modalities (video, audio, footstep, acceleration, gravitational force, directionality, etc.). Among them, acceleration measurement is reasonably accurate, robust, cheap, and easy to do. It has been well established that in an unrestricted environment the most widely used method for effective gait analysis is performed using an accelerometer. This sensor is often combined with a gyro and magnetometer in a small and compatible inertial measurement unit (IMU).

The measuring instruments for quantitative gait analysis have been integrated into human recognition as well as clinical decision-making systems for assessing pathologies manifested by gait abnormalities. Recent advances in wearable sensors, especially inertial body sensors, have paved the path for a promising future gait analysis [1]. Possibly the most important advantage of using gait sensors compared to gait observation using video cameras is that they allow the subject to enjoy the free-living environment over a long period while being monitored.

Despite some recent techniques in human recognition through gait analysis using wearable sensors, e.g. [2–4], a large number of current studies have been dedicated to patient monitoring, such as those with ankle fracture [5], fall injuries [6], osteoarthrosis [7], ataxic [8], multiple sclerosis [9], hip arthroplasty [10], geriatric [11], post recovery [12], and Parkinson's [13–16]. In addition, gait and posture monitoring for athletes has become a significant area of research in sport science [17, 18] mainly for enhancing the capability of athletes and preventing their injuries.