Quantifying Circadian Aspects of Mobility-Related Behavior in Older Adults by Body-Worn Sensors—An “Active Period Analysis”

Disruptions of circadian motor behavior cause a significant burden for older adults as well as their caregivers and often lead to institutionalization. This cross-sectional study investigates the association between mobility-related behavior and subjectively rated circadian chronotypes in healthy older adults. The physical activity of 81 community-dwelling older adults was measured over seven consecutive days and nights using lower-back-worn hybrid motion sensors (MM+) and wrist-worn actigraphs (MW8). A 30-min and 120-min active period for the highest number of steps (MM+) and activity counts (MW8) was derived for each day, respectively. Subjective chronotypes were classified by the Morningness-Eveningness Questionnaire into 40 (50%) morning types, 35 (43%) intermediate and six (7%) evening types. Analysis revealed significantly earlier starts for the 30-min active period (steps) in the morning types compared to the intermediate types (p ≤ 0.01) and the evening types (p ≤ 0.01). The 120-min active period (steps) showed significantly earlier starts in the morning types compared to the intermediate types (p ≤ 0.01) and the evening types (p = 0.02). The starting times of active periods determined from wrist-activity counts (MW8) did not reveal differences between the three chronotypes (p = 0.36 for the 30-min and p = 0.12 for the 120-min active period). The timing of mobility-related activity, i.e., periods with the highest number of steps measured by hybrid motion sensors, is associated to subjectively rated chronotypes in healthy older adults. The analysis of individual active periods may provide an innovative approach for early detecting and individually tailoring the treatment of circadian disruptions in aging and geriatric healthcare.

Soft Origami Optical-Sensing Actuator for Underwater Manipulation

Soft robots are ideal for underwater manipulation in sampling and other servicing applications. Their unique features of compliance, adaptability, and being naturally waterproof enable robotic designs to be compact and lightweight, while achieving uncompromized dexterity and flexibility. However, the inherent flexibility and high nonlinearity of soft materials also results in combined complex motions, which creates both soft actuator and sensor challenges for force output, modeling, and sensory feedback, especially under highly dynamic underwater environments. To tackle these limitations, a novel Soft Origami Optical-Sensing Actuator (SOSA) with actuation and sensing integration is proposed in this paper. Inspired by origami art, the proposed sensorized actuator enables a large force output, contraction/elongation/passive bending actuation by fluid, and hybrid motion sensing with optical waveguides. The SOSA design brings two major novelties over current designs. First, it involves a new actuation-sensing mode which enables a superior large payload output and a robust and accurate sensing performance by introducing the origami design, significantly facilitating the integration of sensing and actuating technology for wider applications. Secondly, it simplifies the fabrication process for harsh environment application by investigating the boundary features between optical waveguides and ambient water, meaning the external cladding layer of traditional sensors is unnecessary. With these merits, the proposed actuator could be applied to harsh environments for complex interaction/operation tasks. To showcase the performance of the proposed SOSA actuator, a hybrid underwater 3-DOFs manipulator has been developed. The entire workflow on concept design, fabrication, modeling, experimental validation, and application are presented in detail as reference for wider effective robot-environment applications.

Models of a hybrid wheeled hopping self-balanced robot

Combining wheeled structure with hopping mechanism, this paper purposes a self-balanced hopping robot with hybrid motion pattern. The main actuator which is the cylindrical cam, optimized by particle swarm optimization (PSO), is equipped with the motor to control the hopping motion. Robotic system dynamics model is established and solved by Lagrangian method. After linearization, control characteristics of the system is obtained by classical control theory based on dynamics equations. By applying Adams and Matlab to simulate the system, hopping locomotion and self-balanced capability are validated respectively, and result shows that jump height can reach 750 mm theoretically. Then PID control scheme is developed and specific models of hardware and software are settled down accordingly. Finally, prototype is implemented and series of hopping experiments are conducted, showing that with different projectile angle, prototype can jump 550 mm in height and 460 mm in length, transcending majority of other existing hopping robots.