Development and Validation of Chest Patch Sensor for Physiological Signal Measurement and Sleep Apnea Evaluation
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 180
- 试验地点
- 1
- 主要终点
- Respiratory Rate
研究概览
简要总结
The existing PranaQ system utilizes a fingertip sensor that captures PPG(Photoplethysmography) and accelerometer data, and its clinical validation is well-established. While PPG alone has shown effectiveness in diagnosing obstructive sleep apnea, its limited data channels restrict comprehensive evaluation. For instance, it struggles to link apnea events with body position or differentiate between central and obstructive sleep apnea.
To address these limitations, the PranaQ system incorporates new sensors, specifically the chest patch sensor, to monitor respiratory movements via accelerometer signals. The additional respiration signal has the potential to improve diagnostic accuracy for apnea through additional information from respiratory effort.
详细描述
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:
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Subjects must be 18 years of age or older.
排除标准
- •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
结局指标
主要结局
Respiratory Rate
时间窗: one night
PSG recording estimated respiratory rate as ground truth to compare with the C-TraQ-generated respiratory rate.
Sleep Position
时间窗: One night
Sleep Position measured by PSG as ground truth to compare with C-TraQ generated sleep position
AHI
时间窗: One night
Technician labeled AHI based on PSG signal to compare with PranaQ system's prediction.
次要结局
未报告次要终点