## 4 Defines and Clarifies the Problems--Why Is Biomechanical One Different from Other Biofeedback?
### Challenges Faced by Developing Wearables for Biomechanical Feedback  
The current sensing development has shown its potential to mitigate problematic constraints of biofeedback devices on human movement and demonstrated its great promise to expand the capabilities of biofeedback to motor-skill learning [5]. The successes in health and physiotherapy [26; 29; 64; 65] suggest that biomechanical wearables will become a reality in human motor learning and training in sports and arts. However, the transition from the simple motor skills training to the complicated ones would face several challenges. It is no doubt that the most challenge for developing biomechanical wearables is the practicality in sports and arts performance. Any device attached to human body will supply certain constraints for our movement and alternate the movement control in a way that may not reach the goal of training. Currently, the reliable 3D motion capture technology requires around 40 markers for motor skills quantification and characterization [52; 59; 60; 66]. Even the non-ideal test condition cannot be substituted by simply replacing the \(\sim\)40 markers (sphere shape of 9 mm in diameter and almost weightless) with wearables, because the weight and volume of current wearables (e.g., IMUs) can cause unknown experimental artifacts. Therefore, how to apply fewer wearables (e.g., 4-6) for accurately rebuilding sports and arts motor skills would be the primary focus for the development of wearables in human motor-skill learning. While the use of the \(\sim\)40 motion-capture markers can directly quantify complicated motor skills, there is no direct way for using 4-6 wearables to reach the same goal. The second challenge is the identification of motor control patterns. In sports and arts activities, the motor control patterns exhibit the characteristic wherein either gross or fine motor control appears to be dominant. In most sports, it is reasonable to conceive that the majority of activities (e.g., running, jumping and throwing) mainly rely upon large muscles (i.e., gross motor control), where smaller muscles function in significant stabilizing roles. Fewer activities, like shooting, rely mainly on smaller muscle group coordination (i.e., fine motor control) where gross motor control supplies foundational support or is nearly arrested [44; 51]. In the case of music performance (e.g., playing the piano or the violin) there is visibly co-dependent interaction of both gross and fine motor control with dynamic interchange of roles depending on the musical context [45; 51]. To complicate matters further, because fine arts performance (e.g., music) unfolds over time, during which all motor control must be guided, performers' motor behaviors must be part of a contextual, forward-planned process. At the same time, since it is undesirable for performers to merely act as mechanical executors of instructions on a printed page [67], they must maintain sufficient flexibility to adapt to and accommodate circumstantial developments. At the highest levels of complexity, adaptation will include immediate forward re-planning. Thus, music performance must be considered a process, not a reconstruction; a reality that creates significant, but not insurmountable, challenges for researchers who apply scientific techniques to fine arts performance. Fine arts performance places more demands on sensing technology than those activities that are dominated by gross motor control in sports. Therefore, wearable sensors are gaining endless interest nowadays in sports [5; 7], whereas, they are still sporadic in arts performance [39; 68]. The third challenge is the expert-knowledge (i.e., compensatory strategies depending on an individual anthropometry and physical condition) in complicated motor skills learning. Motor control in sports and arts are acknowledged to be activities requiring complex behavior and long-time motor control development [14; 42; 59].