Deconstructing Commercial Wearable Technology: Contributions toward Accurate and Free-Living Monitoring of Sleep

Abstract

Despite prolific demands and sales, commercial sleep assessment is primarily limited by the inability to "measure" sleep itself; rather, secondary physiological signals are captured, combined, and subsequently classified as sleep or a specific sleep state. Using markedly different approaches compared with gold-standard polysomnography, wearable companies purporting to measure sleep have rapidly developed during recent decades. These devices are advertised to monitor sleep via sensors such as accelerometers, electrocardiography, photoplethysmography, and temperature, alone or in combination, to estimate sleep stage based upon physiological patterns. However, without regulatory oversight, this market has historically manufactured products of poor accuracy, and rarely with third-party validation. Specifically, these devices vary in their capacities to capture a signal of interest, process the signal, perform physiological calculations, and ultimately classify a state (sleep vs. wake) or sleep stage during a given time domain. Device performance depends largely on success in all the aforementioned requirements. Thus, this review provides context surrounding the complex hardware and software developed by wearable device companies in their attempts to estimate sleep-related phenomena, and outlines considerations and contributing factors for overall device success.

Keywords: accuracy; activity tracker; consumer product; physiological monitoring; sleep; smartwatch; wearable device; wearable sensors.

Figure 1

Systematic occurrences during wake and sleep. The figure demonstrates the minor physiological differences between wake and each of the sleep stages. Normal structural progression, displayed in the hypnogram at the top of the figure provides context surrounding the frequent shifts between states, and the subsequent reliance for accurately capturing physiological trends. Prominent physiological trends often characteristic of these individual states, which are each traditionally measured via separate methods, are comparable including brain activity, cardiac patterns (heart rate and blood pressure), respirations, eye movement, and muscle tone. REM physiology depicted is most representative of phasic REM. (BP, blood pressure; HR, heart rate; Hz, hertz; N1, non-rapid eye movement stage 1; N2, non-rapid eye movement stage 2; N3, non-rapid eye movement stage 3; REM, rapid eye movement).

Figure 2

Arrangements of Photoplethysmography (PPG) Sensor Components. The two primary arrangements of PPG sensors, Reflective and Transmissive, as they pertain to the position of the light source and sensor in relation to target blood vessels. Reflective arrangements are further segregated based upon the relative positioning of the light source and sensor as either direct or angled.

Figure 3

A comparison of cardiovascular signals in wearable devices. The electrocardiogram (ECG) waveform is shown relative to the volumetric waveform obtained via photoplethysmography (PPG). Of note, the volumetric changes that are demonstrated in the PPG waveform captured at a distal anatomical location travel slower than the electrical impulses that are captured by ECG, resulting in a slight delay of features, though highly proportional to that of ECG.