**1. Introduction**

Wearable and wireless systems, such as smartphones and portable media devices, have been demonstrated as functional wireless accelerometer and gyroscope platforms for quantifying human movement endeavors, such as gait, tendon reflex response, movement disorder, and rehabilitation exercise. Further evolution of the technology capability has been demonstrated with the integration of machine learning for attaining classification accuracy [1–3]. The success

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

of these applications derives from preliminary research, development, testing, and evaluation of wireless accelerometer nodes that are essentially wearable for similar scenarios [4].

Inertial sensors such as accelerometers were originally proposed for the quantification of human movement, however at the time of this perspective they were not sufficiently evolved. The technology evolution of accelerometer systems proceeded in tandem with disparate industries relative to the biomedical, rehabilitation, and health industry [4, 5]. Quantification of rehabilitation status can facilitate the modification of a therapy intervention, especially with the expert clinical acuity of a trained expert, however traditional quantification apparatus, such as gait analysis quantification equipment, is generally restricted to a clinical environment [6, 7]. The role of the accelerometer system steadily progressed with the biomedical, rehabilitation, and health community [8]. Eventually with the development of wireless technology supporting inertial sensors, such as accelerometers and gyroscopes, other techniques, such as tethering, became effectively outmoded [9].

The wireless accelerometer has been successfully demonstrated as a wearable system for the quantification of human movement [4]. Tandem operated wireless accelerometer systems have been successfully applied to the quantified evaluation of hemiplegic gait [10–12]. Other associated endeavors have demonstrated the role of wireless accelerometers for quantifying reflex response and even reflex latency [13–19]. Further testing and evaluation has revealed the utility of wireless accelerometers for quantifying movement disorder tremor, such as for Parkinson's disease [20, 21]. Further evolution of the capability of wearable and wireless applications is featured through the research, development, testing, and evaluation of smartphones and portable media devices as wireless accelerometer and gyroscope platforms [1–3, 22].

Ever since the origins of the smartphone, one of its well known features is the observation that the screen will shift orientation based on movement and position. This capability is due to its inertial sensor, originally consisting of an accelerometer and now also a gyroscope. With this feature noted LeMoyne and Mastroianni sought to utilize this inertial sensor package to characterize human movement, much like their previous application of wireless accelerometers for similar endeavors [1–3, 22].
