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Over the last few decades, a growing number of studies have used wearable technologies, such as inertial and pressure sensors, to investigate various domains of music experience, from performance to education. In this paper, we systematically review this body of literature using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method. The initial search yielded a total of 359 records. After removing duplicates and screening for content, 23 records were deemed fully eligible for further analysis. Studies were grouped into four categories based on their main objective, namely performance-oriented systems, measuring physiological parameters, gesture recognition, and sensory mapping. The reviewed literature demonstrated the various ways in which wearable systems impact musical contexts, from the design of multi-sensory instruments to systems monitoring key learning parameters. Limitations also emerged, mostly related to the technology's comfort and usability, and directions for future research in wearables and music are outlined. [ABSTRACT FROM AUTHOR]

Backgroud: Discharge planning from the hospital of frail older patients is an important step to avoid inappropriate long‐stay hospitalizations and to prevent the risks related to the prolonged hospitalization. In this frame, we developed an experimental trial—'PRO‐HOME', a multicomponent programme of interventions for multimorbid and polytreated hospitalized older patients. Aim: The main aim of the study was to develop a protected discharge facility using a mini apartment equipped with advanced architectural and technological components to reduce the length of hospital stay of older participants (aged 65+ years old) admitted to the hospital for an acute event, deemed stable and dischargeable. Materials and Methods: This is a pilot randomized controlled study, comparing 30 hospitalized participants included in a multidimensional, transitional care programme based on information and communication technologies to 30 patients in standard usual care until hospital discharge. Results: We presented the study design of the PRO‐HOME programme, including architectural and technological components, the enrolment procedures, the components of the intervention that is physical activity, cognitive training and life‐style education and the evaluation method of the intervention based on the Comprehensive Geriatric Assessment to explore the changes in the individual domains that are target of the multicomponent intervention. Conclusions: The final results will suggest whether the PRO‐HOME programme represents a useful and feasible intervention to reduce the length of hospital stay of multimorbid and polytreated hospitalized older patients and improve their physical and cognitive performances and overall quality of life. Patient or Public Contribution: Due to the characteristics of the population of interest of the PRO‐HOME study, we involved in the study design and programme of the activities the participants enrolled in a previous smart home‐based project named MoDiPro carried‐out during a 3‐year period. The elderly participants from the local population involved were asked, by means of focus groups, for feedback on their experience in MoDiPro, and their suggestions were integrated into the design phase of the current PRO‐HOME project. The focus groups included open group interviews with a qualitative collection of the patients' feedback so that the participants could interact with each other. [ABSTRACT FROM AUTHOR]

Learning to play and perform a music instrument is a complex cognitive task, requiring high conscious control and coordination of an impressive number of cognitive and sensorimotor skills. For professional violinists, there exists a physical connection with the instrument allowing the player to continuously manage the sound through sophisticated bowing techniques and fine hand movements. Hence, it is not surprising that great importance in violin training is given to right hand techniques, responsible for most of the sound produced. In this paper, our aim is to understand which motion features can be used to efficiently and effectively distinguish a professional performance from that of a student without exploiting sound-based features. We collected and made freely available a dataset consisting of motion capture recordings of different violinists with different skills performing different exercises covering different pedagogical and technical aspects. We then engineered peculiar features and trained a data-driven classifier to distinguish among two different levels of violinist experience, namely beginners and experts. In accordance with the hierarchy present in the dataset, we study two different scenarios: extrapolation with respect to different exercises and violinists. Furthermore, we study which features are the most predictive ones of the quality of a violinist to corroborate the significance of the results. The results, both in terms of accuracy and insight on the cognitive problem, support the proposal and support the use of the proposed technique as a support tool for students to monitor and enhance their home study and practice. [ABSTRACT FROM AUTHOR]