Movement characterisation with accelerometry for improved paediatric sleep assessment

Abstract

Actigraphy is increasingly used to non-invasively estimate sleep quality in children with a suspected sleep disorder. Commercial actigraphs summarise wrist movement, conventionally measured with a uni-axial accelerometer, within a fixed epoch (typically 30s). Wake is subsequently identified as epochs of increased activity and sleep is identified as epochs of inactivity. This classification framework has some distinct limitations: actigraphy misclassifies activity during sleep as wake, and inactivity during wake (i.e. quiet rest) as sleep. In this thesis we will address these limitations by investigating three hypotheses. Firstly, uni-axial accelerometry measured solely at the wrist restricts prediction accuracy, since movements orthogonal to the measurement axis, or occurring elsewhere on the body, cannot be detected. Utilising multisite tri-axial accelerometry may consequently improve sleep and wake prediction. Secondly, there are movement characteristics that can di↵erentiate sleep from wake because the physiological nature of these movements di↵er. Identifying these characteristics may reduce false wake detections. Finally, physiological and pathological events such as apnoeas, hypopneas and transient arousals may be associated with sleep movements that contribute to false wake detections. Exploring this association may consequently explain the presence of some sleep movements.In order to address the hypotheses, 38 participants (27 male, aged 5 16 years) were recruited from children attending the sleep laboratory for suspected sleep-disordered breathing. These children were studied concurrently with polysomnography and a custom system (synchronised to within 0.1s) that recorded raw tri-axial accelerometry data (8 bit, 100Hz, ±2G) simultaneously at the left index fingertip, left wrist, upper thorax, left ankle and left great toe.The first analysis compared the accuracy of predicting sleep and wake epochs with uniaxial, tri-axial, and multisite accelerometry. Tri-axial versions of the conventional 30s epoch summaries were derived and compared to conventional uni-axial accelerometry. Multisite data were explored and verified using two feature selection algorithms with the tri-axial summaries for each accelerometer. Classification performance was significantly improved when incorporating additional accelerometers, and measuring movement with tri-axial accelerometry (Kappa agreement for multisite, tri-axial and uni-axial accelerometry: 0.565(0.231), 0.402(0.141) and 0.268(0.210), p < 0.05). Tri-axial accelerometry has clear benefits with no increase in cost or invasiveness. Although multisite accelerometry provides additional performance benefits, these benefits come at the expense of system complexity and patient discomfort.iii Moving away from epoch-by-epoch predictions, the second analysis assessed wake detection on a movement-by-movement basis. Localised spectral characteristics of raw segmented wrist movements were identified using the discrete wavelet transform. Characteristics that significantly di↵...