STUDY OBJECTIVES: Consumer home sleep trackers provide a great opportunity for longitudinal objective sleep monitoring. Nonwearable sleep devices cause little to no disruption in the daily life routine and need little maintenance. However, their validity needs further investigation. This study aims to evaluate the accuracy of sleep outcomes of EMFIT Quantified Sleep (QS), an unobtrusive nonwearable sleep tracker based on ballistocardiography, against polysomnography. METHODS: 62 sleep-lab patients underwent a single clinical polysomnography with measures simultaneously collected through polysomnography and EMFIT QS. Resting heart rate, total sleep time, wake after sleep onset, sleep onset latency, and duration in sleep stages, collected from the 2 devices, were compared using paired t-tests and their agreement analyzed using Bland-Altman plots. Additionally, continuous heart rate and sleep stages in 30-seconds epochs were evaluated. RESULTS: EMFIT QS data loss occurred in 47% of participants. In the remaining 33 participants (15 women, with mean age of 53.7 ± 16.5 years), EMFIT QS overestimated total sleep time by 177.5 ± 119.4 minutes (p<0.001) and underestimated wake after sleep onset by 44.74 ± 68.81 minutes (P < .001). It accurately measured average resting heart rate and was able to distinguish sleep onset latency with some accuracy. However, the agreement between EMFIT QS and polysomnography on sleep-wake detection was low (kappa = 0.13, P < .001), EMFIT QS failed to distinguish sleep stages. CONCLUSIONS: A consensus between polysomnography and EMFIT QS was found in sleep onset latency and average heart rate. There was significant discrepancy and lack of consensus in other sleep outcomes. These findings indicated that further development is necessary before using EMFIT QS in clinical and research settings. CLINICAL TRIAL REGISTRATION: Registry: Australian New Zealand Clinical Trials Registry; Name: Sleep parameter validation of a consumer home sleep monitoring device, EMFIT Quantified Sleep (QS), against Polysomnography; URL: https://www.anzctr.org.au/ACTRN12621000600842.aspx; Identifier: ACTRN12621000600842. CITATION: Kholghi M, Szollosi I, Hollamby M, Bradford D, Zhang Q. A validation study of a ballistocardiograph sleep tracker against polysomnography. J Clin Sleep Med. 2022;18(4):1203-1210.
STUDY OBJECTIVES: Consumer home sleep trackers provide a great opportunity for longitudinal objective sleep monitoring. Nonwearable sleep devices cause little to no disruption in the daily life routine and need little maintenance. However, their validity needs further investigation. This study aims to evaluate the accuracy of sleep outcomes of EMFIT Quantified Sleep (QS), an unobtrusive nonwearable sleep tracker based on ballistocardiography, against polysomnography. METHODS: 62 sleep-lab patients underwent a single clinical polysomnography with measures simultaneously collected through polysomnography and EMFIT QS. Resting heart rate, total sleep time, wake after sleep onset, sleep onset latency, and duration in sleep stages, collected from the 2 devices, were compared using paired t-tests and their agreement analyzed using Bland-Altman plots. Additionally, continuous heart rate and sleep stages in 30-seconds epochs were evaluated. RESULTS: EMFIT QS data loss occurred in 47% of participants. In the remaining 33 participants (15 women, with mean age of 53.7 ± 16.5 years), EMFIT QS overestimated total sleep time by 177.5 ± 119.4 minutes (p<0.001) and underestimated wake after sleep onset by 44.74 ± 68.81 minutes (P < .001). It accurately measured average resting heart rate and was able to distinguish sleep onset latency with some accuracy. However, the agreement between EMFIT QS and polysomnography on sleep-wake detection was low (kappa = 0.13, P < .001), EMFIT QS failed to distinguish sleep stages. CONCLUSIONS: A consensus between polysomnography and EMFIT QS was found in sleep onset latency and average heart rate. There was significant discrepancy and lack of consensus in other sleep outcomes. These findings indicated that further development is necessary before using EMFIT QS in clinical and research settings. CLINICAL TRIAL REGISTRATION: Registry: Australian New Zealand Clinical Trials Registry; Name: Sleep parameter validation of a consumer home sleep monitoring device, EMFIT Quantified Sleep (QS), against Polysomnography; URL: https://www.anzctr.org.au/ACTRN12621000600842.aspx; Identifier: ACTRN12621000600842. CITATION: Kholghi M, Szollosi I, Hollamby M, Bradford D, Zhang Q. A validation study of a ballistocardiograph sleep tracker against polysomnography. J Clin Sleep Med. 2022;18(4):1203-1210.
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