High-Throughput Electrospinning System| A “rigid-flexible" iontronic pressure sensorwith high sensitivity and wide responserange for hand dysfunction rehabilitationtraining

Professors Wang Bin and Zhang Xiuqin from Beijing Institute of Fashion Technology: "Rigid-Flexible" Microstructured Iontronic Pressure Sensor with High Sensitivity, High Resolution and Wide Response Range

Real-time monitoring of hand rehabilitation progress is crucial for enhancing patient confidence and promoting optimal recovery in patients with hand dysfunction. However, traditional rehabilitation training methods often lack intuitive feedback mechanisms, making it difficult for patients to accurately assess their training progress and effectiveness. Therefore, developing a monitoring method that can accurately reflect the real-time rehabilitation training status of patients with hand dysfunction is of great significance.

Recently, Professor Wang Bin and Professor Zhang Xiuqin's team from the School of Materials Design and Engineering at Beijing Institute of Fashion Technology published their latest research titled "A 'Rigid-Flexible' Iontronic Pressure Sensor with High Sensitivity and Wide Response Range for Hand Dysfunction Rehabilitation Training" in Chemical Engineering Journal. The study proposed a modulus-differentiated "rigid-flexible" system combined with iontronic sensing mechanism to develop a microstructured iontronic pressure sensor (MIPS) featuring high sensitivity (546.58 kPa⁻¹), high resolution (0.025 kPa), and wide response range (0-1200 kPa). Additionally, MIPS demonstrated strain interference resistance (7.3%), fast response time (87 ms), excellent cycling stability (10,000 cycles@1.0 kPa), and good wearability comfort.

Based on these multiple advantages, the team developed an intelligent recognition glove (M-IRG) for monitoring hand dysfunction rehabilitation training. The glove can accurately track hand movements (including bending, extension and grasping objects) and monitor the recovery level of patients with hand dysfunction.

Figure 1 shows the preparation process and application schematic of MIPS. The ionic dielectric layer was obtained by blending ionic liquid with PBST using conventional electrospinning. Furthermore, high-modulus gradient-sized polylactic acid microspheres (PLA MPs) were loaded onto the surface of low-modulus poly(butylene terephthalate)-co-poly(butylene succinate) nanofiber membranes (PBST NMs) via electrospraying, forming a "deformation generation and diffusion" mechanism that further delays deformation saturation. Subsequently, conductive ink was coated using screen printing technology and dried to obtain the microstructured electrode layer. Finally, ultrasonic welding technology was used for final encapsulation to obtain the iontronic pressure sensor with multiple excellent performances (as shown in Figures 2 and 3).

Figure 1: Manufacturing process and application schematic of MIPS

Figure 2: Physical performance tests of MIPS

Figure 3: Sensing performance of MIPS

As shown in Figure 4, leveraging MIPS' ability to accurately capture subtle human motion signals, an intelligent recognition glove (M-IRG) was developed to assist rehabilitation training for patients with hand dysfunction. During rehabilitation training, M-IRG can capture pressure changes generated by fingers in different bending states, thereby identifying different gesture changes and providing reliable basis for evaluating patients with hand dysfunction. The Carroll Upper Extremity Function Test (UEFT) was then used to assess patients' hand rehabilitation level through block grasping, promoting hand function rehabilitation training and evaluation. This demonstrates great application prospects in the fields of intelligent medical monitoring and wearable electronic devices.

Figure 4: M-IRG for monitoring hand dysfunction rehabilitation training