Signal processing

Human–computer interaction

Electrical engineering

Engineering

Control engineering

Electronics

Artificial intelligence

Biosensor

Nanotechnology

Materials science

Programming language

Decoupling (probability)

Sensitivity (control systems)

Electronic engineering

SIGNAL (programming language)

Robotics

Computer science

Bioelectronics

Digital signal processing

Robot

Computer hardware

Advanced Science

Highly sensitive and multimodal sensors have recently emerged for a wide range of applications, including epidermal electronics, robotics, health-monitoring devices and human-machine interfaces. However, cross-sensitivity prevents accurate measurements of the target input signals when a multiple of them are simultaneously present. Therefore, the selection of the multifunctional materials and the design of the sensor structures play a significant role in multimodal sensors with decoupled sensing mechanisms. Hence, this review article introduces varying methods to decouple different input signals for realizing truly multimodal sensors. Early efforts explore different outputs to distinguish the corresponding input signals applied to the sensor in sequence. Next, this study discusses the methods for the suppression of the interference, signal correction, and various decoupling strategies based on different outputs to simultaneously detect multiple inputs. The recent insights into the materials' properties, structure effects, and sensing mechanisms in recognition of different input signals are highlighted. The presence of the various decoupling methods also helps avoid the use of complicated signal processing steps and allows multimodal sensors with high accuracy for applications in bioelectronics, robotics, and human-machine interfaces. Finally, current challenges and potential opportunities are discussed in order to motivate future technological breakthroughs.

Multimodal Sensors with Decoupled Sensing Mechanisms