Complex hand dexterity is fundamental to our interactions with the physical, social, and cultural environment. Dexterity can be an expression of creativity and precision in a range of activities, including musical performance. Little is understood about complex hand dexterity or how virtuoso expertise is acquired, due to the versatility of movement combinations available to complete any given task. This has historically limited progress of the field because of difficulties in measuring movements of the hand. Recent developments in methods of motion capture and analysis mean it is now possible to explore the intricate movements of the hand and fingers. These methods allow us insights into the neurophysiological mechanisms underpinning complex hand dexterity and motor learning. They also allow investigation into the key factors that contribute to injury, recovery and functional compensation. The application of such analytical techniques within musical performance provides a multidisciplinary framework for purposeful investigation into the process of learning and skill acquisition in instrumental performance. These highly skilled manual and cognitive tasks present the ultimate achievement in complex hand dexterity. This paper will review methods of assessing instrumental performance in music, focusing specifically on biomechanical measurement and the associated technical challenges faced when measuring highly dexterous activities.

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Previous researches show that a scratchpad memory device consumed less energy than a cache device with the same capacity. In this article, we locate the scratchpad memory (SPM) in the top level of the memory hierarchy to reduce the energy consumption. To take the advantage of a SPM, we address two issues of utilizing a SPM. First, the program's locality should be improved. The second issue is SPM management. To tackle these two issues, we present a hardware/software framework for dynamically allocating both instructions and data in SPM. The software flow could be divided into three phases: locality improving, locality extraction, and runtime SPM management. Without modifying the original compiler and the source code, we improve the locality of a program. An optimization algorithm is proposed to extract the SPM allocations. At runtime, an SPM management program is employed. In hardware, an address translation logic (ATL) is proposed to reduce the overhead of SPM management. The results show that the proposed framework can reduce energy delay product (EDP) by 63%, on average, when compared with the traditional cache architecture. The reduction in EDP is contributed by properly allocating both instructions and data in SPM. By allocating only instructions in SPM, the EDPs are reduced by 45%, on average. By allocating only data in SPM, the EDPs are reduced by 14%, on average.

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