The monitoring of treadmill walking energy expenditure (EE) plays an important role in health evaluations and management, particularly in older individuals and those with chronic diseases. However, universal and highly accurate prediction methods for walking EE are still lacking. In this paper, we propose an ensemble neural network (ENN) model that predicts the treadmill walking EE of younger and older adults and stroke survivors with high precision based on easy-to-obtain features. Compared with previous studies, the proposed model reduced the estimation error by 13.95% and 66.20% for stroke survivors and younger adults, respectively. Furthermore, a contactless monitoring system was developed based on Kinect, mm-wave radar, and ENN algorithms, and the treadmill walking EE was monitored in real time. This ENN model and monitoring system can be combined with smart devices and treadmill, making them suitable for evaluating, monitoring, and tracking changes in health during exercise and in rehabilitation environments.
Magnetic soft robots (MSRs) can achieve controllable shape-morphing by magnetic programming to the magnetic elastomer. However, the magnetization profile is usually implemented on a continuous region and is unchangeable. The deformation and function design of MSR hence is limited. This study presents a programmable magnetic pixel soft robot (MPSR). By encapsulating liquid-metal/NdFeB composites into a Silicone shell, the thermal-magnetic response functional film with lattice-structure is fabricated, with the highest pixel resolution of 1 × 1 mm2. A piece of laser-assisted magnetic programming equipment is developed to implement magnetic encoding on discrete regions of the film. Therefore, a mathematical model is proposed to help calculate the magnetic codes according to the preset end shape. At last, several pixel-structure MPSRs are prepared and tested. Experimental results show that using the magnetic encoding technique, we can reconfigure the deformations and functions of the robot. This study provides a basis for the programmed shape regulation and motion design of the soft robot.
