Validity of a commercial wearable sleep tracker in adult insomnia disorder patients and good sleepers

Kang, Seung-Gul; Kang, Jae Myeong; Ko, Kwang Pil; Park, Seon Cheol; Mariani, Sara; Weng, Jia

doi:10.1016/j.jpsychores.2017.03.009

Cited by 132 publications

(87 citation statements)

References 17 publications

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“…Another study reported that measurements obtained using the UP device correlated with total sleep time ( r = 0.63) and time in bed ( r = 0.79), but did not correlate with measurements of deep sleep, light sleep or sleep efficiency (Gruwez et al, 2017 ). Several studies have reported similar findings for the Fitbit Flex™ device (Montgomery-Downs et al, 2012 ; Mantua et al, 2016 ; Kang et al, 2017 ). In a validation study of the OURA ring, it was shown to record similar total sleep time, sleep latency onset and wake after sleep onset, and had high sensitivity for detecting sleep (0.96).…”

Section: Technologies For Monitoring and Promoting Better Sleepmentioning

confidence: 56%

A Critical Review of Consumer Wearables, Mobile Applications, and Equipment for Providing Biofeedback, Monitoring Stress, and Sleep in Physically Active Populations

2018

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The commercial market for technologies to monitor and improve personal health and sports performance is ever expanding. A wide range of smart watches, bands, garments, and patches with embedded sensors, small portable devices and mobile applications now exist to record and provide users with feedback on many different physical performance variables. These variables include cardiorespiratory function, movement patterns, sweat analysis, tissue oxygenation, sleep, emotional state, and changes in cognitive function following concussion. In this review, we have summarized the features and evaluated the characteristics of a cross-section of technologies for health and sports performance according to what the technology is claimed to do, whether it has been validated and is reliable, and if it is suitable for general consumer use. Consumers who are choosing new technology should consider whether it (1) produces desirable (or non-desirable) outcomes, (2) has been developed based on real-world need, and (3) has been tested and proven effective in applied studies in different settings. Among the technologies included in this review, more than half have not been validated through independent research. Only 5% of the technologies have been formally validated. Around 10% of technologies have been developed for and used in research. The value of such technologies for consumer use is debatable, however, because they may require extra time to set up and interpret the data they produce. Looking to the future, the rapidly expanding market of health and sports performance technology has much to offer consumers. To create a competitive advantage, companies producing health and performance technologies should consult with consumers to identify real-world need, and invest in research to prove the effectiveness of their products. To get the best value, consumers should carefully select such products, not only based on their personal needs, but also according to the strength of supporting evidence and effectiveness of the products.

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Section: Technologies For Monitoring and Promoting Better Sleepmentioning

confidence: 56%

A Critical Review of Consumer Wearables, Mobile Applications, and Equipment for Providing Biofeedback, Monitoring Stress, and Sleep in Physically Active Populations

2018

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“…Many studies have examined the validity and reliability of these devices in laboratories [18,19,21,63,70] and in participants' own living environment [55]. Validation studies on previous wearable wristbands such as Fitbit Charge HR [19] and Jawbone UP [46] revealed that these devices generally underestimated wake time while overestimated sleep time and sleep efficiency in healthy adults, and their measurements of sleep stages had no correlation to medical devices [21,48,55,57]. Whereas achieving better accuracy has been the main goal of many sleep-tracking technologies, it remains unknown if better accuracy increases perceived believability.…”

Section: Sleep Tracking and Monitoring Technologiesmentioning

confidence: 99%

How Does Fitbit Measure Brainwaves

Liang

Ploderer

2020

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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Consumer sleep-tracking devices provide an unobtrusive and affordable way to learn about personal sleep habits. Recent research focused primarily on the information provided by such devices, i.e., whether the information is accurate and meaningful to people. However, little is known about how people judge the credibility of such information, and how the functionality and the design may influence such judgements. Hence, the aim of this research was to examine how consumers assess the credibility of sleep-tracking devices. We conducted a qualitative study with 22 participants who tracked their sleep for 3 nights with three different devices: Fitbit Charge 2, Neuroon EEG, and SleepScope, a medical sleep monitor. Based on semi-structured interviews, we found that people assess the credibility of sleep-tracking devices based not only on the credibility of sleep data per se, but also on device functionality, interface design and physical appearance. People found it difficult to judge credibility, because of the complexities of sleep stages and micro-arousals (sleep fallacy) and the black boxed nature of devices (black box fallacy), and also because of the misalignment between objective sleep measures and subjective sleep quality. We discuss the significance of design and functionality on the credibility of personal health technologies and highlight design challenges and opportunities to enhance their credibility. CCS Concepts: • Human-centered computing → Empirical studies in HCI.

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“…The use of these wearable wristbands in healthcare yields high expectations, but it is unclear whether these expectations are warranted [ 7 ]. There are several commercially available wristbands that potentially provide a range of HRV parameters, such as the Empatica E4 wristband [ 7 – 9 ], the Polar watch, [ 10 , 11 ], and the Fitbit watch [ 12 – 14 ] among others. These devices provide a potentially simple and promising tool for data acquisition in both research and clinical studies [ 15 – 18 ], but are artefact prone due to movement [ 2 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

Validity of the Empatica E4 Wristband to Measure Heart Rate Variability (HRV) Parameters: a Comparison to Electrocardiography (ECG)

et al. 2020

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Wearable monitoring devices are an innovative way to measure heart rate (HR) and heart rate variability (HRV), however, there is still debate about the validity of these wearables. This study aimed to validate the accuracy and predictive value of the Empatica E4 wristband against the VU University Ambulatory Monitoring System (VU-AMS) in a clinical population of traumatized adolescents in residential care. A sample of 345 recordings of both the Empatica E4 wristband and the VU-AMS was derived from a feasibility study that included fifteen participants. They wore both devices during two experimental testing and twelve intervention sessions. We used correlations, cross-correlations, Mann-Whitney tests, difference factors, Bland-Altman plots, and Limits of Agreement to evaluate differences in outcomes between devices. Significant correlations were found between Empatica E4 and VU-AMS recordings for HR, SDNN, RMSSD, and HF recordings. There was a significant difference between the devices for all parameters but HR, although effect sizes were small for SDNN, LF, and HF. For all parameters but RMSSD, testing outcomes of the two devices led to the same conclusions regarding significance. The Empatica E4 wristband provides a new opportunity to measure HRV in an unobtrusive way. Results of this study indicate the potential of the Empatica E4 as a practical and valid tool for research on HR and HRV under non-movement conditions. While more research needs to be conducted, this study could be considered as a first step to support the use of HRV recordings provided by wearables.

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Validity of a commercial wearable sleep tracker in adult insomnia disorder patients and good sleepers

Cited by 132 publications

References 17 publications

A Critical Review of Consumer Wearables, Mobile Applications, and Equipment for Providing Biofeedback, Monitoring Stress, and Sleep in Physically Active Populations

A Critical Review of Consumer Wearables, Mobile Applications, and Equipment for Providing Biofeedback, Monitoring Stress, and Sleep in Physically Active Populations

How Does Fitbit Measure Brainwaves

Validity of the Empatica E4 Wristband to Measure Heart Rate Variability (HRV) Parameters: a Comparison to Electrocardiography (ECG)

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