Real-time signal processing in MEMS sensor-based motion analysis systems

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Fältnamn	Indikatorer	Metadata
000		04716nam a2200325 4500
001		oai:DiVA.org:mdh-42619
003		SwePub
008		190208s2019 \| \|\|\|\|\|\|\|\|\|\|\|000 \|\|eng\|
020		a 9789174854213q print
024	7	a https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-426192 URI
040		a (SwePub)mdh
041		a engb eng
042		9 SwePub
072	7	a vet2 swepub-contenttype
072	7	a dok2 swepub-publicationtype
100	1	a Du, Jiayingu Mälardalens högskola,Inbyggda system4 aut0 (Swepub:mdh)jdu01
245	1 0	a Real-time signal processing in MEMS sensor-based motion analysis systems
264	1	a Västerås :b Mälardalen University,c 2019
338		a electronic2 rdacarrier
490	0	a Mälardalen University Press Dissertations,x 1651-4238 ;v 285
520		a This PhD thesis focuses on real-time signal processing for hardware-limited micro-electro-mechanical system (MEMS) sensor-based human motion analysis systems. The aim of the thesis is to improve the signal quality of MEMS gyroscopes and accelerometers by minimizing the effects of signal errors, considering the hardware limitations and the users' perception.MEMS sensors such as MEMS gyroscopes and MEMS accelerometers are important components in motion analysis systems. They are known for their small size, light weight, low power consumption, low cost, and high sensitivity. This makes them suitable for wearable systems for measuring body movements. The data can further be used as input for advanced human motion analyses. However, MEMS sensors are usually sensitive to environmental disturbances such as shock, vibration, and temperature change. A large portion of the MEMS sensor signals actually originate from error sources such as noise, offset, null drift and temperature drift, as well as integration drift. Signal processing is regarded as the major key solution to reduce these errors. For real-time signal processing, the algorithms need to be executed within a certain specified time limit. Two crucial factors have to be considered when designing real-time signal processing algorithms for wearable embedded sensor systems. One is the hardware limitations leading to a limited calculation capacity, and the other is the user perception of the delay caused by the signal processing.Within this thesis, a systematic review of different signal error reduction algorithms for MEMS gyroscope-based motion analysis systems for human motion analysis is presented. The users’ perceptions of the delay when using different computer input devices were investigated. 50 ms was found as an acceptable delay for the signal processing execution in a real-time motion analysis system. Real-time algorithms for noise reduction, offset/drift estimation and reduction, improvement of position accuracy and system stability considering the above mentioned requirements, are presented in this thesis. The algorithms include a simplified high-pass filter and low-pass filter, a LMS algorithm, a Kalman filter, a WFLC algorithm, two simple novel algorithms (a TWD method and a velocity drift estimation method), and a novel combination method KWT. Kalman filtering was found to be efficient to reduce the problem of temperature drift and the WFLC algorithm was found the most suitable method to reduce human physiological tremor and electrical noise. The TWD method resulted in a signal level around zero without interrupting the continuous movement signal. The combination method improved the static stability and the position accuracy considerably. The computational time for the execution of the algorithms were all perceived as acceptable by users and kept within the specified time limit for real-time performance. Implementations and experiments showed that these algorithms are feasible for establishing high signal quality and good system performance in previously developed systems, and also have the potential to be used in similar systems.
650	7	a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Signalbehandling0 (SwePub)202052 hsv//swe
650	7	a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Signal Processing0 (SwePub)202052 hsv//eng
653		a elektronik
653		a Electronics
700	1	a Lindén, Maria,c Professor,d 1965-u Mälardalens högskola,Inbyggda system4 ths0 (Swepub:mdh)mln04
700	1	a Grip, Helena,c Docentu Norrlands universitetssjukhus/Umeå University4 opn
710	2	a Mälardalens högskolab Inbyggda system4 org
856	4	u https://mdh.diva-portal.org/smash/get/diva2:1286907/FULLTEXT02.pdfx primaryx Raw objecty fulltext
856	4 8	u https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-42619

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