Most people spend about 25% to 33% of their lives sleeping. Since sleep quality is strongly correlated with productivity, mood and hygiene, sleep technology – especially wearables – has a booming market presence.
Different types of sleep monitoring technology. Image courtesy of Perez-Pozuelo et al. and nature
In contrast to polysomnography (PSG), the gold standard clinical method for assessing sleep, wearable sleep technology falls under the category of consumer sleep technology (CST). For electrical engineers, CST means an integrated system with low power consumption, considerable processing capacity and miniaturized space on the circuit board.
Companies like Google, ResMed, EarlySense, and Fitbit are actively working on developing such devices. Now, Google claims that a new radar chip with built-in sleep analysis capabilities could be the key to wider CST adoption.
The benefits of Consumer Sleep Tech over clinical analysis
The advantage of Consumer Sleep Tech over clinical methods (such as PSG) for understanding sleep quality is the observer effect: observing patients in a laboratory setting can lead to inaccuracies in such studies. With CST, consumers do not have to be in a laboratory setting and benefit from the convenience, ease of use and low cost.
A graph that shows accuracy versus user load. PSG is the most accurate, but it also has the highest user load. Image courtesy of Perez-Pozuelo et al. and nature
Clinically, sleep consists of five phases: wakefulness (W), non-rapid eye movement (NREM –– N1, N2, N3) and rapid eye movement (REM).
An example of sleep phases that are tracked in a wearable. Image courtesy Fitbit
Sleep Tech classifies and analyzes these sleep phases and provides the user with an informative summary.
Multi-sensory vs. motion sensor approaches to sleeping
There are two common approaches to analyzing sleep at the hardware design level: multi-sensory and motion-sensor-based approaches.
The multisensory approach uses different sensors, such as B. optical photoplethysmography (PPG) sensors, temperature sensors and vibration sensors. Meanwhile, the motion sensor approach typically relies on an accelerometer and a radar sensor to measure wakefulness and sleep. In CST it is possible to combine both approaches.
The place of piezoelectric sensors in non-portable devices
CST is also available in the form of non-wearables. Non-wearable devices may contain bed sensors, where a piezoelectric sensor can monitor biological signals such as heart rate, breathing, and body movements.
When a piezoelectric sensor is subjected to dynamic loading, it creates a charge or voltage and is analyzed to indicate duration, phase or quality of sleep. TE Connectivity creates such sensors in a strip with a piezoelectric PVDF polymer film embedded in or placed on a mattress. Its thickness is on the order of 50 microns, which the company claims is flexible and imperceptible for practical purposes.
A graph showing the varying charge or output voltages detected by piezoelectric sensors for different biometric vibrations. Image courtesy of TE Connectivity
Although there are many companies developing components and technologies for CST, Google is trying to innovate the world of sleep diagnostics.
Google starts project solos
A new, innovative CST from Google is Project Soli. Soli is a low-power radar technology that consists of a frequency-modulated 60 GHz millimeter-wave continuous wave radar transceiver unit (FMCW) first incorporated into Pixel 4 phones (most recently in Nest Hub).
Solis radar chip project. Image used courtesy of Google
The radar emits an electromagnetic wave that hits the object and reflects back to the radar antenna. The frequency spectrum of the reflected signal contains a large amount of information that represents the distance and speed of objects within the scene.
Google claims that a wide variety of movements can be recorded and characterized – from body movements to breathing. A convolutional neural network (CNN) differentiates between three states: absence, wakefulness and sleep. Sleep detection is available as an opt-in in Nest Hub.
The Nest Hub also uses microphones, temperature sensors, and light sensors to record coughs, snores, changes in room temperature, and lighting – all factors that can affect sleep. The data collected is processed on the device and not on servers, creating a data protection layer associated with the product.
An outline view of a system with solos. Image used courtesy of Google
Another benefit of Nest Hub’s sleep detection is that it’s contactless, making it convenient for users who don’t want to wear smartwatches while they sleep. One downside, however, is that Soli cannot yet differentiate between low-movement activities like sleeping and reading, as it doesn’t rely on heart rate measurements and direct motion detection to assess sleep.
Extension of the reach of consumer sleep technology
With the new version of CST technology, Google hopes that Soli can expand the concept of generating sleep data and lead to further advances in CST beyond wearables. While Consumer Tech is not intended to diagnose or treat sleep-related disorders, it can help users understand the quality of daily sleep and the factors that affect sleep.
More about Sleep Tech and Biometric Monitoring
Interested in sleep sensor technology or other types of biometric sensors used in wearables? You can find more discussions below.
