The development and accuracy of the THIM device for estimating sleep and wakefulness

Author: Hannah Scott

  • Thesis download: available for open access on 6 Aug 2021.

Scott, Hannah, 2020 The development and accuracy of the THIM device for estimating sleep and wakefulness, Flinders University, College of Education, Psychology and Social Work

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Chronic insomnia is a pervasive and burdensome sleep disorder that is not being adequately treated at present in Australia. There is a need for practical yet effective treatments for insomnia to address this serious personal and societal burden. Intensive Sleep Retraining (ISR) is a brief but effective laboratory-based behavioural treatment for sleep onset insomnia that involves a series of rapid sleep onsets facilitated by near-total sleep deprivation. In conjunction with Re-Time Pty. Ltd., we have developed a wearable device called THIM which promises to administer ISR in the home environment. To successfully administer ISR, THIM must be able to accurately estimate sleep onset and wake the patient at the appropriate time to achieve rapid sleep onsets. Additionally, THIM can passively monitor sleep and wakefulness during the sleep period. If THIM accurately monitors sleep, this data could be incorporated into insomnia treatment. This dissertation discussed the development and accuracy of THIM for estimating sleep onset and for monitoring nocturnal sleep and wakefulness compared to the gold standard of objective sleep measurement, polysomnography (PSG).

Chapter 2 was the first systematic review to examine the accuracy of wearable devices for the estimation of sleep onset latency (SOL) compared to PSG. The review concluded that devices measuring behavioural sleep onset were most suitable for the administration of ISR because they consistently overestimated PSG-determined SOL, but with little variability between individuals compared to other wearable devices. This finding justified the method that THIM relies upon to estimate sleep onset for the purposes of ISR: the measurement of behavioural responsiveness to minimal intensity vibratory stimuli.

Chapter 3 described the development and accuracy of the THIM device for estimating SOL in comparison to PSG. From the findings of Study 1, the THIM algorithm was refined and its accuracy confirmed in Study 2. THIM showed much closer agreement to PSG than other behavioural devices that use auditory stimuli and larger hand/wrist movements as behavioural responses. The final version of the algorithm had a discrepancy with PSG-SOL of less than one minute on average, which was consistent across two nights of testing. THIM appears to be accurate enough to administer ISR, but its accuracy for individuals with insomnia needs to be investigated in future research.

Chapter 4 presented a quantitative electroencephalography analysis of the data from Chapter 3 to characterise sleep microstructure through a more fine-grained lens than traditional 30-second epoch sleep staging. This study was the first to examine the correspondence between sleep microstructure and responses to minimal intensity vibratory stimuli during the process of falling asleep. The findings indicated that participants had increases in higher frequency brainwaves (alpha, sigma and beta) when they responded to the vibratory stimulus and increases in delta activity when they did not respond to the stimulus across all sleep stages. This suggests that a shift to wakefulness or an arousal occurred prior to, or coincident with, the onset of the vibratory stimulus, which may explain why participants responded to the stimulus. Thus, THIM was able to detect brief arousals during sleep stages that traditional sleep scoring criteria would overlook, which were a common occurrence during N1 sleep. THIM is accurate for detecting brief periods of wakefulness. These findings further supported the conceptualisation of N1 sleep as a transitional, fluctuating state between wake and sleep.

Chapter 5 described the refinement of the THIM sleep tracking function. It was the first study to test the accuracy of THIM for estimating sleep and wakefulness over a nocturnal sleep period compared to PSG. THIM was similar in accuracy for estimating sleep and wake compared to wrist-based actigraphy devices. However, THIM showed a greater tendency to underestimate total sleep and overestimate total wake compared to other actigraphy devices. There was high variability in the accuracy of THIM between individuals, yet this was not explained by whether participants were good or poor sleepers.

Chapter 6 extended the findings of Chapter 5 by examining the consistency in the accuracy of THIM over three nights compared to PSG. THIM showed consistently high sensitivity, specificity and accuracy compared to PSG across all nights. However, THIM produced consistently and significantly lower estimations of sleep efficiency due to higher estimations of wake after sleep onset. The improvement of the accuracy of THIM for estimating wake is required to render the device useful for objective sleep monitoring.

Together, the findings of this dissertation indicate that THIM may be able to successfully administer ISR. The findings also suggest that improvements to the THIM sleep tracking algorithm are required for the device to provide accurate enough sleep tracking data to support the treatment of insomnia. Future research is required to investigate the efficacy of THIM-administered ISR and the accuracy of THIM sleep tracking in the home environment for individuals with insomnia. The long-term goal of this research program is to create an effective yet practical device to support the treatment of insomnia. This dissertation is the proof-of-concept step in the development of THIM.

Keywords: wearable device, intensive sleep retraining, consumer sleep technology, insomnia, behavioural treatment, actigraphy, polysomnography, sleep measurement.

Subject: Psychology thesis

Thesis type: Doctor of Philosophy
Completed: 2020
School: College of Education, Psychology and Social Work
Supervisor: Leon Lack