David C. Mack

Development and Preliminary Validation of Heart Rate and Breathing Rate Detection Using a Passive, Ballistocardiography-Based Sleep Monitoring System

Techniques such as ballistocardiography (BCG) that can provide noninvasive long-term physiological monitoring have gained interest due to a growing recognition of adverse effects from poor sleep and sleep disorders. The noninvasive analysis of physiological signals (NAPS) system is a BCG-based monitoring system developed to measure heart rate, breathing rate, and musculoskeletal movement that shows promise as a general sleep analysis tool. Overnight sleep studies were conducted on 40 healthy subjects during a clinical trial at the University of Virginia. The NAPS systems measures of heart rate and breathing rate were compared to ECG, pulse oximetry, and respiratory inductance plethysmography (RIP). The subjects were split into a training dataset and a validation dataset, maintaining similar demographics in each set. The NAPS system accurately detected heart rate, averaged over the prescribed 30-s epochs, to within less than 2.72 beats per minute of ECG, and accurately detected breathing rate, averaged over the same epochs, to within 2.10 breaths per minute of RIP bands used in polysomnography.

A Passive and Portable System for Monitoring Heart Rate and Detecting Sleep Apnea and Arousals: Preliminary Validation

The National Institutes of Health (NIH) Sleep Disorders Research Plan expresses a need for methods that can non-invasively monitor sleep characteristics. Forty subjects were tested using a novel, passive ballistocardiography-based system during an overnight study. We examined our systems ability to measure heart rate as compared to EKG while we also investigated our systems apnea and arousal detection capabilities as compared to conventional polysomnography. We found a strong correlation (r=0.972, p<0.0001) in average heart rate computed over 480 thirty-second epochs when our method was compared to EKG. Additionally, we achieved a sensitivity of 89.2% and specificity of 94.6% in the automated detection of apneas. Similarly we attained a sensitivity of 77.3% and a specificity of 96.2% in the detection of arousals. These preliminary results demonstrate the effectiveness of our portable ballistocardiography-based system as compared to polysomnography and show promise that high quality sleep assessment can be performed in a home environment

Psychosocial Impact of Passive Health Status Monitoring on Informal Caregivers and Older Adults Living in Independent Senior Housing

This paper describes a study designed to assess some psychosocial impacts of monitoring technology on seniors living in independent senior housing. monitoring systems were installed, in 25 independent living units in an apartment complex, to track the activities of daily living (ADLs) and key alert conditions of residents. Activity reports were sent to informal caregivers. Residents (N=25) were assessed using the satisfaction with life scales (SWLS) instrument, informal caregivers (N=26) were assessed using modified caregiver strain index (CSI) and caregiver burden interview (CBI) instruments, before and after the installation of the monitoring system. Paired t-test for means was applied to the pre- and post-monitoring scores of SWLS, CSI, and CBI. The Wilcoxon matched-pairs signed-ranks nonparametric test was applied to compare the number of informal care hours pre- and post-monitoring. No statistically significant increase was observed on SWLS results. No significant changes in CSI and CBI scores were detected. There was a statistically significant increase in the number of informal care hours provided by the informal caregivers of monitored individuals. The results indicate that monitoring technologies could have enabled informal caregivers to provide more care for their loved ones without increasing their burdens, strain levels or negatively affecting their quality of life

Sleep assessment using a passive ballistocardiography-based system: Preliminary validation

Quantitative sleep analysis through the use of polysomnography is a well established standard. Finding new ways to approach this, especially over multiple nights, is becoming more important due to a growing recognition of adverse effects from poor sleep and sleep disorders. The Non-Invasive Analysis of Physiological Signals (NAPSTM) system is a ballistocardiography-based monitoring system developed to measure heart rate, breathing rate and musculoskeletal movement that shows promise as a general sleep analysis tool. Overnight sleep studies were conducted on 20 healthy subjects during a validation clinical trial which compared the NAPS system to actigraphy, using polysomnography as the gold standard. The NAPS system [κ = 3D 0.478; 95% CI (0.463, 0.494); p-value < 0.001] outperformed actigraphy [κ = 3D 0.344; 95% CI (0.324, 0.358); p-value < 0.001], largely due to better performance in distinguishing sleep onset times as determined by polysomnography [NAPS mean bias estimate: -2.5 epochs; 95% CI (-16.8, 11.9); p = 3D 0.725 | Actigraphy mean bias estimate: -33.6 epochs; 95% CI (-57.4, -9.7); p = 3D 0.016)].