Ultra-Low-Power and Wide-Operating-Voltage-Window Capacitive Piezotronic Sensor through Coupling of Piezocharges and Depletion Widths for Tactile Sensing.

The rapid growth of Artificial Intelligence and Internet of Things (AIoT) demands the development of ultra-low-power devices for future advanced technology. In this study, we introduce a capacitive piezotronic sensor specifically designed for tactile sensing, which enables an ultra-low-voltage operation at nearly 0 reading bias conditions with a consistent response within a wide voltage range. This sensor directly detects capacitance changes induced by piezocharges, reflecting perturbation of the effective depletion width, and ensures ultralow power capability by eliminating the necessity of turning on the Schottky diode for the first time. The dynamic response of the sensor demonstrates ultralow power capability and immunity to triboelectric interference, making it particularly suitable for tactile sensing applications in robotics, prosthetics, and wearables. This study provides valuable insights and design guidelines for future ultra-low-power thin-film-based capacitive piezotronic/piezophototronic devices for tactile sensing.

Quality of life in depression: predictive models.

The purpose of this study was to examine the predictive factors of quality of life for inpatients with depressive disorders. Eighty-three patients (mean age 44; 73% female) with depressive disorders were recruited from the psychosomatic ward of a medical center in the northern part of Taiwan. The predictive models of this study were established by encompassing three constructs: clinical variables, demographics, and perceived competence. The outcome variables of this study included an overall quality of life score and four domains' scores of the World Health Organization Quality of Life-brief version (WHOQOL-BREF). Stepwise regression analysis was used to identify significant factors related to the outcome variables. The results showed that there were five distinct models for the various domains of the quality of life. The predictive variables of the final model for overall quality of life included: the Beck Anxiety Inventory, the Canadian Occupational Performance Measure-satisfaction, and the Occupational Self Assessment-self. For the physical domain of the quality of life model, the adjusted Beck Depression Inventory-II, the Beck Anxiety Inventory, and the Activity of Daily Living Inventory were the significant predictors. In the psychological domain, the adjusted Beck Depression Inventory-II and age were the predictive factors. The adjusted Beck Depression Inventory-II, the Beck Anxiety Inventory and the Occupational Self Assessment-environment were the predictors for the social domain of quality of life. Finally, the adjusted Beck Depression Inventory-II, age, and the Occupational Self Assessment-environment were the predictors for the environmental domain of quality of life. The significance of the perceived competence variables in the quality of life of patients with depression indicates that occupational therapy intervention is warranted.