{"id":{"repo_id":"nus","oai_identifier":"oai:scholarbank.nus.edu.sg:10635/149514"},"canonical_url":"https://search.dev.ndltd.org/etd/nus/oai:scholarbank.nus.edu.sg:10635/149514","repository":{"repo_id":"nus","name":"National University of Singapore","base_url":"https://scholarbank.nus.edu.sg/oai/request"},"display":{"title":"MULTI-CHANNEL CDMA-LIKE CAPACITIVE SENSOR INTERFACE CIRCUITS","abstract":"Internet-of-things (IoT) has been a key driving force for the semiconductor industry. Its development is governed by three components, i.e. advanced sensors, low-power and low-cost sensor interface circuits and efficient wireless connections. This thesis introduces a CDMA-like period modulation multi-capacitive-sensor interface circuit, which targets at the IoT applications. The proposed architecture can simultaneously read in 16 capacitive sensors and provide the combined 16 digitized output in one sample. By correlating 16 successive digitized samples with orthogonal codes in post-processing, it can then demodulate the digitized output of the 16 capacitive sensors separately at the receiver end. This potentially leads to 16 times smaller data throughput for efficient wireless data transmission compared to 16-channel time-interleave counterpart. The sharing of analog front-end and quantization block also helps achieving good power and area efficiency.","abstract_html":"Internet-of-things (IoT) has been a key driving force for the semiconductor industry. Its development is governed by three components, i.e. advanced sensors, low-power and low-cost sensor interface circuits and efficient wireless connections. This thesis introduces a CDMA-like period modulation multi-capacitive-sensor interface circuit, which targets at the IoT applications. The proposed architecture can simultaneously read in 16 capacitive sensors and provide the combined 16 digitized output in one sample. By correlating 16 successive digitized samples with orthogonal codes in post-processing, it can then demodulate the digitized output of the 16 capacitive sensors separately at the receiver end. This potentially leads to 16 times smaller data throughput for efficient wireless data transmission compared to 16-channel time-interleave counterpart. 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By correlating 16 successive digitized samples with orthogonal codes in post-processing, it can then demodulate the digitized output of the 16 capacitive sensors separately at the receiver end. This potentially leads to 16 times smaller data throughput for efficient wireless data transmission compared to 16-channel time-interleave counterpart. 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