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XeThru UWB radar sensors deliver hospital-grade data

Back in September, we planned a little experiment which involved sending our colleague Magnus to Trondheim’s St. Olavs Hospital to take part in a hospital sleep monitoring study called Polysomnography (PSG). The goal of this experiment was to compare the data extracted from the PSG study with the XeThru respiration sensor data and highlight how the results closely matched.

Polysomnography is a multi-parametric test used in the study of sleep and as a diagnostic tool in sleep medicine. It monitors many body functions including brain, eye movements, muscle activity or skeletal muscle activation and heart rhythm during sleep. Magnus, our brave colleague, was selected to take part of this experiment and with the help of a hospital staff from the department of Neurology at St Olavs Hospital, a series of sensors were placed on his body.

Four types of sensors were used to record electrical activity of the brain, measure eye movements, record muscle tension and record the electrical activity of the heart. In addition to these standard PSG sensors, respiration rate was measured with the use of belts and nasal airflow pressure transducers. A sound probe was placed over the neck to record snoring and a pulse oximeter over the middle finger to determine blood oxygen levels.

During the testing night, Magnus slept with the PSG sensors attached to his body that were continuously monitoring his sleep and respiration. A XeThru respiration module was also placed at his bed side table that would simultaneously monitor Magnus’ respiration and movement at a distance.


Key finding - Identical RPM readings:

The data received from the hospital was set as the “gold standard” and we were delighted to see that the XeThru sensor provided virtually identical RPM readings compared to the PSG study. This significant finding proves that XeThru’s sensor delivers advanced hospital-grade data and is clearly on a par with the professional sleep study.

Virtually identical RPM readings from PSG and XeThru

Figure 1: Virtually identical RPM readings from PSG and XeThru


Key finding - Improved movement readings:

Improved movement readings by XeThru was also observed from the comparison. While PSG captures body movement with the use of several sensors, XeThru was able to observe further movements with just one sensor scanning the entire body. In the below graph, we see that virtually all PSG movements are captured by XeThru, however the red bars show all additional movements detected by the sensor. This confirms XeThru’s unique high sensitivity feature, as it captures minute movements from the entire body.

XeThru vs PSG - Movement

Figure 2: XeThru vs PSG - Movement


Key finding - Improved sleep stage identification:

To fully assess a night’s sleep and understand sleep-related disorders, it is important to understand the different stages of sleep. The XeThru sensor was indeed able to provide high quality sleep stage identification using both respiration and movement, and later translate that data into sleep stages (live and continuous). The colored bars below depict the different sleep stages (deep sleep vs REM) that XeThru was able to identify from its advanced movement readings.

XeThru Hypnography

Figure 3: XeThru Hypnography


Key finding - Sleep quality:

It is evident that sleep quality can have a substantial impact on one’ general quality of life and even life expectancy. Any interrupted periods of deep sleep and REM sleep will hinder the body’s natural course of renewal and restoration. Lack of deep sleep will also cause the body to have more deep sleep next time, at the expense of REM. With a detailed sleep stage analysis, a general overview of one’s sleep quality can be derived.

XeThru Hypnography matrix

Table 1: XeThru Hypnography Matrix


This revealing experiment helped us strengthen our position with the XeThru UWB radar sensor as a respiration monitoring device comparable to medical-grade standards. Not only did it match all the data from the PSG study, but it also provided improved overall readings to XeThru’s benefit. We were also able to solidify the sensitivity aspect of the sensor, which enabled an improved sleep stage identification practice and ultimately paint a clearer picture of sleep quality.

You can also check this video for a behind the scenes look of the sleep experiment:

Special thanks to Trondheim’s St. Olavs Hospital for coordinating this experiment and to our colleague Magnus who jumped at the sleep challenge, and who had to endure a not-so-pleasant night in the making!