Detecting Accuracy of Accelerometer and Gyroscope Wearable Shimmer Sensors using Linear Regression

Smart Wearable can measures physical activities by analyzing the user’s body movements which requires existing sensors such as accelerometer and gyroscope in order to secure perilous data so that it should not go missing at the point of high speed rotation or high impact. Accelerometer is a sensor that has been generally recognized as suitable and practical in smart wearable devices to measure and assess human physical activities. Wearable accelerometer sensor affords easily moveable systems that stream real-time data. The gyroscope sensor track human movement and activity and improves its accuracy. In this paper, we are comparative analyzing the commercially available SHIMMER3 wearable 3rd generation sensors raw data of age under 71-80+ people from two different sensors i.e. accelerometer and gyroscope and modeling it with machine learning approach of linear regression.

GWAS in 446,118 European adults identifies 78 genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates

Sleep is an essential homeostatically-regulated state of decreased activity and alertness conserved across animal species, and both short and long sleep duration associate with chronic disease and all-cause mortality1,2. Defining genetic contributions to sleep duration could point to regulatory mechanisms and clarify causal disease relationships. Through genome-wide association analyses in 446,118 participants of European ancestry from the UK Biobank, we discover 78 loci for self-reported sleep duration that further impact accelerometer-derived measures of sleep duration, daytime inactivity duration, sleep efficiency and number of sleep bouts in a subgroup (n=85,499) with up to 7-day accelerometry. Associations are enriched for genes expressed in several brain regions, and for pathways including striatum and subpallium development, mechanosensory response, dopamine binding, synaptic neurotransmission, catecholamine production, synaptic plasticity, and unsaturated fatty acid metabolism. Genetic correlation analysis indicates shared biological links between sleep duration and psychiatric, cognitive, anthropometric and metabolic traits and Mendelian randomization highlights a causal link of longer sleep with schizophrenia.