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消费者家庭睡眠监测心冲击图 Beddit 睡眠追踪器的睡眠参数评估准确性:一项验证研究。

Sleep Parameter Assessment Accuracy of a Consumer Home Sleep Monitoring Ballistocardiograph Beddit Sleep Tracker: A Validation Study.

机构信息

Department of Psychology and Speech-Language Pathology, University of Turku, Finland.

Division of Medicine, Department of Pulmonary Diseases, Turku University Hospital, Turku, Finland.

出版信息

J Clin Sleep Med. 2019 Mar 15;15(3):483-487. doi: 10.5664/jcsm.7682.

Abstract

STUDY OBJECTIVES

Growing interest in monitoring sleep and well-being has created a market for consumer home sleep monitoring devices. Additionally, sleep disorder diagnostics, and sleep and dream research would benefit from reliable and valid home sleep monitoring devices. Yet, majority of currently available home sleep monitoring devices lack validation. In this study, the sleep parameter assessment accuracy of Beddit Sleep Tracker (BST), an unobtrusive and non-wearable sleep monitoring device based on ballistocardiography, was evaluated by comparing it with polysomnography (PSG) measures. We measured total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE). Additionally, we examined whether BST can differentiate sleep stages.

METHODS

We performed sleep studies simultaneously with PSG and BST in ten healthy young adults (5 female/5 male) during two non-consecutive nights in a sleep laboratory.

RESULTS

BST was able to distinguish SOL with some accuracy. However, it underestimated WASO and thus overestimated TST and SE. Also, it failed to discriminate between non-rapid eye movement sleep stages and did not detect the rapid eye movement sleep stage.

CONCLUSIONS

These findings indicate that BST is not a valid device to monitor sleep. Consumers should be careful in interpreting the conclusions on sleep quality and efficiency provided by the device.

摘要

研究目的

对睡眠和健康监测的兴趣日益浓厚,催生了家用睡眠监测设备市场。此外,睡眠障碍诊断和睡眠与梦境研究也将受益于可靠且有效的家用睡眠监测设备。然而,目前大多数可用的家用睡眠监测设备都缺乏验证。在这项研究中,通过与多导睡眠图(PSG)测量值进行比较,评估了基于心动冲击描记术的非侵入性、非穿戴式睡眠监测设备 Beddit 睡眠追踪器(BST)的睡眠参数评估准确性。我们测量了总睡眠时间(TST)、睡眠潜伏期(SOL)、睡眠后觉醒时间(WASO)和睡眠效率(SE)。此外,我们还研究了 BST 是否可以区分睡眠阶段。

方法

我们在睡眠实验室中对 10 名健康的年轻成年人(5 名女性/5 名男性)进行了两次非连续的睡眠研究,同时进行了 PSG 和 BST 测量。

结果

BST 能够准确区分 SOL。但是,它低估了 WASO,从而高估了 TST 和 SE。此外,它无法区分非快速眼动睡眠阶段,也无法检测快速眼动睡眠阶段。

结论

这些发现表明,BST 不是监测睡眠的有效设备。消费者在解释该设备提供的关于睡眠质量和效率的结论时应谨慎。

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