Development of a Torso Patch Sensor (C-TraQ) as a Companion Device to a Fingertip Sensor (TipTraQ) for Direct Monitoring of Respiratory Effort

Disease Background Sleep apnea-hypopnea syndrome (SAHS) represents a pervasive and significant public health challenge, affecting a substantial segment of the adult population. Epidemiological data indicate that 34% of men and 17% of women between the ages of 30 and 70 are impacted by this condition. Despite its high prevalence, SAHS remains vastly underdiagnosed and consequently undertreated, leaving a large portion of the affected population vulnerable to its associated health risks.

The established gold standard for the definitive diagnosis of sleep apnea is full-channel polysomnography (PSG). This comprehensive diagnostic procedure necessitates the simultaneous recording of a multitude of physiological and biological signals throughout the night, including electroencephalography (EEG) to monitor brain activity and sleep stages, electrooculography (EOG) for eye movements, electromyography (EMG) for muscle activity, and dedicated sensors for airflow, respiratory effort, and blood oxygen saturation.

However, the clinical utility and accessibility of PSG are severely constrained by several inherent limitations. The study is highly uncomfortable, requiring patients to be affixed with a complex array of over 20 sensors and leads. Crucially, PSG is exclusively a hospital-based procedure, confining patients to an unfamiliar environment which can itself negatively impact natural sleep patterns (the "first-night effect"). Furthermore, the subsequent analysis of the multichannel PSG data is resource-intensive, demanding hours of expert technician time for the meticulous labeling and scoring of individual sleep breathing events, which contributes to its high cost, significant time commitment, and impracticality for widespread population screening or routine follow-up evaluation. These barriers highlight the urgent need for more accessible, less burdensome, and cost-effective diagnostic alternatives for sleep apnea.

Description of PranaQ system

The PranaQ system integrates multiple wearable sensors-one for the fingertip and one for the chest-with a mobile application and an interpretable AI platform. The sensors collect the following data:

• T-TraQ (Fingertip Sensor): Records Photoplethysmography (PPG), accelerometer, and temperature data from the fingertip.
• C-TraQ (Torso Patch Sensor): Also collects PPG, accelerometer, and temperature data. In this study, there are three sensors attached over sternum, abdomen and left subclavicle area.

The PranaQ system, composed of wearable devices and cloud computing, is designed for both home and clinical settings to aid in the evaluation and diagnosis of suspected adult sleep apnea patients, as well as for long-term monitoring. Its function includes recording, storing, and exporting physiological waveforms. After the patient completes the recording, the collected signal data will be sent to the cloud for automatic report generation. The final sleep report will then be sent back to the healthcare provider through a browser-based user interface (PranaQ Expert Panel).

Clinical Evaluation Objectives and Purpose

• Validate the respiration information generated by the C-TraQ (Chest Patch Sensor). The raw signal from the chest patch is accelerometer-based. The respiration rate and waveform generated from the chest patch signal will be compared for consistency with information concurrently obtained from the thorax and abdominal belt collected through the PSG.
• Validate the multi-sensor PranaQ system for the diagnosis of sleep apnea The TST, TRT, ODI, and AHI(both obstructive and central) generated by the PranaQ system will be compared with the results from PSG labeled by a technician.

Inclusion criteria

• Subjects must be 18 years of age or older.

Exclusion criteria

• Opioids use
• Chronic Obstructive Lung Disease, Global Initiative for Chronic Obstructive
• Lung Disease (GOLD) categorization 3 or 4
• Devastating strokes, with a modified Rankin score (mRS) ≥ 4
• Interstitial lung disease