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dc.contributor.authorPal, Mayanken_US
dc.identifier.citationPal, M. (2022). Real-time local muscle fatigue assessment using synaptic transistors. Doctoral thesis, Nanyang Technological University, Singapore.
dc.description.abstractWearable devices have taken up the industry by storm. Not only they aim to detect the early symptoms of common physiological health adversities, but they also help to develop a sense of health awareness among the people. Muscle fatigue is a common indicator of many health abnormalities and if neglected, can lead to long term or even permanent muscle damage, especially in athletes who tend to push the barrier of physical human capabilities. Most methods of muscle fatigue assessment are hospital based, and thus fail to provide valuable indicators while the muscles are being actually undergoing fatigue. This thesis tends to explore the potential for a wearable muscle fatigue sensing system, that can provide indications in real time, and may even be trained to detect fatigue at its very onset. The EMG signals obtained from the muscle under test undergo a change in frequency, which is a well-established phenomenon. Most methods to measure these changes are based on converting the time domain signal to frequency domain on a powerful software used on a PC by using FFT. Synaptic transistors are new class of transistors that are being explored in order to mimic the neuromorphic functions of the mammalian brain. They show time dependent plasticity, and this can be easily linked to frequency dependence in case of ac signal inputs. If the EMG signal output is amplified and fed to the gate of synaptic transistors, the frequency of the EMG signal can be measured in response to a pre-set calibration. This thesis is aimed at attaining a deeper insight into the operations of synaptic transistors and then testing the potential of these transistors for assessing the changes in the frequency of EMG signal which in turn is an important indicator of muscle fatigue. For controlling the frequency regime, in which the transistor exhibits the synaptic characteristics, a novel method of gating the transistor with hydrogels of varying geometrical length has been shown. We show this by characterizing the transistors for pulse duration dependent plasticity. Plasticity is represented here by using presynaptic pulses of varying pulse duration, in different frequency regimes. The frequency of pulsed used covered a wide range from 1 Hz to 10 kHz. The specific value of frequencies chosen, is based on the limits in which the transistors exhibited synaptic characteristics. Firstly, we show the results for pulse duration plasticity, for a normal water gated synaptic transistor, without using any hydrogel cable for mediation. These transistors exhibit plasticity in a broad range from 1 Hz to 10 kHz frequency. The on time of the pulse is increased from 10% to 70% with a step size of 10%. The plasticity progressively increases as the frequency is varied from 1 Hz to 10 kHz frequency region, Thus, we can observe that by increasing the length of the ionic hydrogel cable used for gating the transistor, the curve for gain retention ratio can be shifted towards lower and lower frequency. As a result, for further standalone applications of synaptic transistors, any particular material system can be used, and by employing auxiliary circuit components as has been shown here, the same transistor, with the same material system and configuration, can tuned to operate in different frequency regions.en_US
dc.publisherNanyang Technological Universityen_US
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).en_US
dc.titleReal-time local muscle fatigue assessment using synaptic transistorsen_US
dc.typeThesis-Doctor of Philosophyen_US
dc.contributor.supervisorChen Xiaodongen_US
dc.contributor.schoolSchool of Materials Science and Engineeringen_US
dc.description.degreeDoctor of Philosophyen_US
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