# A Wearable Sonification System to Improve Movement Awareness: A Feasibility Study
## 2 Related Work  
This literature review investigated the developments of wearable technologies and approaches to providing auditory feedback to enhance gait and rehabilitation outcomes through sonification. An earlier study by [PERSON] and [PERSON] [23] used accelerometer signals to detect gait events such as heel strike (HS) and toe off (TO) in a normal gait cycle. To use accelerometers for continuous monitoring or long-term analysis, they developed an algorithm to incorporate the magnitude of the resultant accelerometer signal, obtained from each axis of the three-axis accelerometer, into time-frequency analysis to detect gait events. Their algorithm was validated for its accuracy and robustness using gait experiments conducted in indoor and outdoor environments. The experiment involved gait event detections with varying speeds, terrains, and surface inclinations. However, their algorithm was only developed for a single accelerometer around the ankle. It did not account for the impact due to the left or right foot and the applicability of a multi-accelerometer setup with improved accuracy. Other researchers have found that a gyroscope is the preferred device to detect gait events (HS and TO), because its measurements are not sensitive to the body part where it was placed [26; 27; 28]. [PERSON] et al. [27] developed a low-cost wearable wireless gyroscope worn around the foot and ankle to identify gait events. The gyroscope was coupled with an Arduino Pro Mini for (i) converting raw sensing data to angular rate values, (ii) detecting HS and TO, and (iii) transmitting data to a computer for processing. However, in their experiment, the reliability and accuracy of the wireless gyroscope deteriorated over an extended period. Our investigation identified that the reduced reliability and accuracy of wireless gyroscopes over extended periods could stem from multiple sources. These included the physical deterioration of sensor components, challenges in maintaining system synchronization over time, and accumulated errors and other limitations inherent in the algorithms presented in the literature. Therefore, developing a more resilient algorithmic framework could mitigate these issues, and capitalizing on the advantages of low-cost, single wearable sensing technology could be a feasible solution. Auditory feedback in wearable technology, especially in the form of sonification, has demonstrated its potential to enhance motor coordination and gait rehabilitation [17; 30; 31; 32]. Sonification signals generated according to different types and magnitudes of body motionscan provide crucial feedback, especially during a gait cycle and other time-related activities, to assist a person in the perception of their movements [34,35]. For the last decade, rhythmic auditory cueing has been used to transform human movement patterns into sound to enhance perception accuracy [36]. Auditory feedback has been widely used to allow users to perceive their movement amplitudes and positioning better and to enhance motor recovery during rehabilitation [37, 38, 39] and in the execution, control, and planning of movement [33,36]. Auditory feedback has also been shown to influence postural sway, where acoustic properties of the auditory stimuli might be more influential in reducing sway than any position or velocity information encoded in the stimuli [40, 41, 42]. Auditory feedback has been shown to improve motor performance in skills such as balancing compared to purely visual feedback [43]. Swaving movements outside a balance reference region have been corrected by a tone mapped to this movement acceleration in the mediolateral and posterior-anterior directions [33,41,44]. In the context of [PERSON]'s disease, sonification, especially when incorporating musical elements, has shown promising results in improving balance [32]. Another study [30] highlighted that the presence or absence of auditory cues can facilitate or hinder typical motor patterns and stability in gaze.