Wrist-worn gesture sensing with wearable intelligence

This paper presents an innovative wrist-worn device with machine learning capabilities and a wearable pressure sensor array. The device is used for monitoring different hand gestures by tracking tendon movements around the wrist. Thus, an array of PDMS-encapsulated capacitive pressure sensors is attached to the user to capture wrist movement. The sensors are embedded on a flexible substrate and their readout requires a reliable approach for measuring small changes in capacitance. This challenge was addressed by measuring the capacitance via the switched capacitor method. The values were processed using a programme on LabVIEW to visually reconstruct the gestures on a computer. Additionally, to overcome limitations of tendon’s uncertainty when the wristband is re-worn, or the user is changed, a calibration step based on the Support Vector Machine (SVM) learning technique is implemented. Sequential Minimal Optimization (SMO) algorithm is also applied in the system to generate SVM classifiers efficiently in real-time. The working principle and the performance of the SVM algorithms demonstrate through experiments. Three discriminated gestures have been clearly separated by SVM hyperplane and correctly classified with high accuracy (>90%) during real-time gesture recognition

Nanowire and Fiber Composite Electromechanical Sensor

Fiber or nanowire composites offer many benefits for piezoelectric sensor and actuator applications. Piezoelectric composite is comprised of piezoelectric ceramics lain in polymer matrix. The composite with the piezoelectric ceramics connected in one direction and the polymer in three directions is named as 1-3 composite. 1-3 composites are most ordinary used and the anisotropic alignment of PZT in the composite may substantially lower lateral piezoelectric coupling and increases the sensitivity of the transducer mechanically. Piezoelectric fiber composites are suitable for sensor applications, medical diagnostics and nondestructive testing. Single crystal zinc-oxide nanowires were synthesized through a simple hydrothermal route and subsequently mixed with polyimide matrix to form ZnO nanocomposites. Superimposed a.c. and d.c. electric fields were applied to microscopically tailor the alignment of ZnO nanowires in polyimide matrix to form anisotropic nanocomposites. Piezoresistive property of ZnO nanocomposite was investigated for strain sensor application. A large gauge factor was obtained from the monotonic uniaxial stress-strain experiment for this nanocomposite and it is much higher than that of ordinary metal strain sensor. A low frequency fiber composite vibration sensor was fabricated and experimentally studied. The global parameters of the composite were substituted into lumped and distributed element constituent equations for piezoelectric unimorph to theoretically predict the sensitivity and effective frequency response range of the vibration sensor. An experiment was carried out to validate the result from the theoretical model. The output voltage per unit input displacement keeps stable in a wide frequency range with a suitable damping ratio. This PZT fiber composite sensor was also applied for soft material strain measurement and soft biomaterial surface morphology and elastic modulus characterization. From the theoretical evaluation and experiment result, this strain sensor is suitable for strain measurement with high sensitivity and high softness. A rectangular breathing sensor and an annular breathing sensor were fabricated for breathing rate and depth monitoring. Both sensors were tested under different physiological conditions and measurement results could be utilized for precaution and monitoring of breathing diseases. Both of them are excellent for monitoring breathing rate and depth and be nice choices for daily use and diagnose purpose