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This paper proposes a method for modifying the functionality of conductive fabric by using different weaves on the same materials. After introducing the method, this paper demonstrates its effectiveness using an example involving fabric pressure sensors. The fabric pressure sensors in this paper can alter the electrical properties of a given fabric—while using the same material in both the warp and weft directions—by changing the weaving technique at certain locations within the fabric. Conventional fabric pressure sensors require separate, location-specific outputs; every increase in the number of detection locations requires an increase in the number of detector circuit input cables. However, our fabric pressure sensors can detect location and external force via just three input–output cables.

In this work, we propose a fabric electrode with a special structure that can play the role of a noise reduction filter. Fabric electrodes made of the conductive fabric have been used for long-term ECG measurements because of their flexibility and non-invasiveness, however, due to the large impedance between the skin and the fabric electrodes, noise is easily introduced into the ECG signal. In contrast to conventional work, in which chip-type passive elements are glued to the electrode to reduce noise, the proposed electrode can obtain a noise-reduced ECG by changing the structure of fabric. Specifically, the proposed electrode was folded multiple times to form a capacitor with a capacitance of about 3 nF. It is combined with the skin-electrode impedance to form a low-pass filter. In the experiment, we made a prototype of the electrodes and measured ECG at rest and during EMG-induced exercise. As a result, the SNR values at rest and during exercise were improved about 12.02 and 10.29 dB, respectively, compared with the fabric electrode without special structure. In conclusion, we have shown that changing the fabric electrode structure effectively removes noise in ECG measurement.

A switched-capacitor (SC) capacitance-to-time (C/T) converter used for differential capacitive sensors with improved accuracy is presented in this paper. Using three rather than two time intervals, the circuit can remove the influences of the propagation delay of the comparator the channel charge injection and clock feedthrough due to analog switches, and the finite gain of the op-amp in principle. Then the proposed circuit can perform C/T conversion with high precision. Performances of the proposed circuit are simulated by HSPICE using 0.18 micrometers CMOS process parameters. Simulated results have demonstrated that the gain error is 0.00057 % and the maximum nonlinear error is about 0.0015 % of the full scale. It is also shown that a high-accuracy C/T converter can be realized even when a low-gain amplifier is used. The circuit can relax the restriction on the design of a comparator and an op-amp even for high conversion accuracy. As a result, the power consumption of the circuits can be also reduced.

Burst mode control techniques have been studied for LLC resonant dc-dc converters to improve power conversion efficiencies at light load conditions. However, there are not many studies about how to detect the load conditions at burst mode not even at normal mode, at the primary side of LLC resonant dc-dc converters. In this paper, we propose and implement a lossless load detection technique for normal and burst modes by a novel average input current sensing method at the primary side of LLC resonant converters. Detailed theoretical analysis at normal and burst modes is presented and a load detection circuit is proposed with the consideration of integrated circuits. To verify the analysis, an LLC resonant offline converter with 400 V input and 16 V/10 A output is simulated using PSIM and a prototype board is built. The experimental results show that the proposed load detection technique is valid and practical. As a result, an automatic burst mode control for LLC resonant converters at light load conditions is realized with the proposed average input current sensing method.