In-Memory Tactile Sensor with Tunable Steep-Slope Region for Low-Artifact and Real-Time Perception of Mechanical Signals

Abstract

A tactile sensor needs to perceive static pressures and dynamic forces in real-time with high accuracy for early diagnosis of diseases and development of intelligent medical prosthetics. However, biomechanical and external mechanical signals are always aliased (including variable physiological and pathological events and motion artifacts), bringing great challenges to precise identification of the signals of interest (SOI). Although the existing signal segmentation methods can extract SOI and remove artifacts by blind source separation and/or additional filters, they may restrict the recognizable patterns of the device, and even cause signal distortion. Herein, an in-memory tactile sensor (IMT) with a dynamically adjustable steep-slope region (SSR) and nanocavity-induced nonvolatility (retention time >1000 s) is proposed on the basis of a machano-gated transistor, which directly transduces the tactile stimuli to various dope states of the channel. The programmable SSR endows the sensor with a critical window of responsiveness, realizing the perception of signals on demand. Owing to the nonvolatility of the sensor, the mapping of mechanical cues with high spatiotemporal accuracy and associative learning between two physical inputs are realized, contributing to the accurate assessment of the tissue health status and ultralow-power (about 25.1 μW) identification of an occasionally occurring tremor.

A Discolorable Flexible Synaptic Transistor for Wearable Health Monitoring

“…This approach not only facilitates convenient monitoring of human activities without the need for expensive and complicated integration procedures but also provides a cost-effective and efficient method for managing health conditions. Recent demonstrations have also showcased the possibility of integrating sensing functionalities into EGT devices. ,− This innovation provides opportunities for the further development of all-in-one wearable edge computing systems dedicated to health evaluation. Consequently, wearable electronics based on EGT technologies hold great promise for the advancement of critical healthcare technologies, ultimately improving the quality of life for individuals, especially those necessitating emergency medical attention or ongoing health monitoring …”

Recent Advances in Tactile Sensory Systems: Mechanisms, Fabrication, and Applications

“…However, conventional methods turn to integrating multi-sensory modalities to guarantee accuracy, sensitivity, and effectiveness, which will increase the complexity of circuits, energy consumption, and crosstalk among signals. As shown in Figure 10 d, Hu et al [ 145 ] proposed an in-memory tactile sensor (IMT) with a programmable steep-slope region and retention time of >1000 s based on a mechano-gated transistor. In view of programmability and nonvolatility, the IMT could realize sensing signals on demand, mechanical cue mapping with high spatiotemporal resolution, and associative learning between two physical inputs, leading to precise assessment for patients’ health status with an ultralow power dissipation of ~25.1 μW.…”

“…Schematic diagram of the volatile pristine in-memory tactile sensor (iii) and the nonvolatile PEI de-doped in-memory tactile sensor (iv). Reproduced with permission from Ref [145]…”

Ultralow-cost piezoelectric sensor constructed by thermal compression bonding for long-term biomechanical signal monitoring in chronic mental disorders

“…Recently, propelled by the urgent demand for advanced artificial intelligence and wearable medical devices, flexible wearable devices have attracted considerable attention due to their lightweight and portability. [19][20][21][22][23][24][25] They enable continuous monitoring of physiological signals, thus supporting clinical decisions and enhancing the management of mental health disorders. [26][27][28][29] For example, electroencephalogram (EEG) elec- † Electronic supplementary information (ESI) available.…”