Eating behaviors are closely related to body weight, and eating traits are depicted in three dimensions: dietary restraint, disinhibition, and hunger. The current study aims to explore whether these aspects of eating behaviors are related to intrinsic brain activation, and to further investigate the relationship between the brain activation relating to these eating traits and body weight, as well as the link between function connectivity (FC) of the correlative brain regions and body weight. Our results demonstrated positive associations between dietary restraint and baseline activation of the frontal and the temporal regions (i.e., food reward encoding) and the limbic regions (i.e., homeostatic control, including the hypothalamus). Disinhibition was positively associated with the activation of the frontal motivational system (i.e., OFC) and the premotor cortex. Hunger was positively related to extensive activations in the prefrontal, temporal, and limbic, as well as in the cerebellum. Within the brain regions relating to dietary restraint, weight status was negatively correlated with FC of the left middle temporal gyrus and left inferior temporal gyrus, and was positively associated with the FC of regions in the anterior temporal gyrus and fusiform visual cortex. Weight status was positively associated with the FC within regions in the prefrontal motor cortex and the right ACC serving inhibition, and was negatively related with the FC of regions in the frontal cortical-basal ganglia-thalamic circuits responding to hunger control. Our data depicted an association between intrinsic brain activation and dietary restraint, disinhibition, and hunger, and presented the links of their activations and FCs with weight status.

Triboelectric nanogenerators, as a device that converts mechanical energy into electrical energy, can respond to external pressure stimuli. However, most triboelectric sensors can only perform pressure measurements in a narrow pressure range, which limits their application in multiple scenarios. Here, we proposed a wide-range triboelectric pressure sensor based on the difference in Young’s modulus of the materials and a double-sandwich-structure design. We analyzed the effect of the structural angle at the material surface on the sensor performance and obtained an optimal combination of angles for a double-sandwich-structure sensor. The proposed sensor has outstanding performance including high sensitivity (249.32 mV/kPa), wide range (0–450 kPa), and fast response time (26 ms). Meanwhile, the sensor has a quite low detection limit (8.72 Pa). The designed sensor can be applied not only to the detection of small physiological signals but also to large plantar pressure sensing. A human motion recognition system based on plantar pressure was developed. Moreover, we also designed a convolutional gated recurrent unit model to recognize four human motions with high accuracy (99.42%). This work provides a design idea to extend the range of the triboelectric sensor to meet multiple applications.

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