Development of a Portable Device for Telemonitoring of Physical Activities During Sleep

Unobtrusive online monitoring of sleep at home

We describe an online sleep monitoring service, based on unobtrusive ballistocardiography (BCG) measurement in an ordinary bed. The novelty of the system is that the sleep tracking web application is based on measurements from a fully unobtrusive sensor. The BCG signal is measured with a piezoelectric film sensor under the mattress topper, and sent to the web server for analysis. Heart rate and respiratory variation, activity, sleep stages, and stress reactions are inferred based on the signal. The sleep information is presented to the user along with measurements of the sleeping environment (temperature, noise, luminosity) and user-logged tags (e.g. stress, alcohol, exercise). The approach is designed for long-term use at home, allowing users to follow the development of their sleep over months and years. The service has also a medical use, as sleep disorder patients can be measured for long periods before and after interventions.

A Gaussian model for movement detection during sleep

Quality of sleep is an important attribute of an individual's health state and its assessment is therefore a useful diagnostic feature. Changes in the patterns of mobility in bed during sleep can be a disease marker or can reflect various abnormal physiological and neurological conditions. This paper describes a method for detection of movement in bed that is evaluated on data collected from patients admitted for regular polysomnography. The system is based on load cells installed at the supports of a bed. Since the load cell signal varies the most during movement, the approach uses a weighted combination of the short-term mean-square differences of each load cell signal to capture the variations in the signal caused by movement. We use a single univariate Gaussian model to represent each class: movement versus non-movement. We assess the performance of the method against manual annotation performed by a sleep clinic technician from seventeen patients. The proposed detection method achieved an overall sensitivity of 97.9% and specificity of 98.7%.

A method for classification of movements in bed

Sleep is characterized by episodes of immobility interrupted by periods of voluntary and involuntary movement. Increased mobility in bed can be a sign of disrupted sleep that may reduce sleep quality. This paper describes a method for classification of the type of movement in bed using load cells installed at the corners of a bed. The approach is based on Gaussian Mixture Models using a time-domain feature representation. The movement classification system is evaluated on data collected in the laboratory, and it classified correctly 84.6% of movements. The unobtrusive aspect of this approach is particularly valuable for longer-term home monitoring against a standard clinical setting.

Wireless portable electrocardiogram and a tri-axis accelerometer implementation and application on sleep activity monitoring

Night-to-night variability of sleep activity requires more home-based portable sleep monitoring instead of clinical polysomnography examination in the laboratory. In this article, a wireless sleep activity monitoring system is described. The system is light and small for the user. Sleep postures, such as supine or left/right side, were observed by a signal from a tri-axis accelerometer. An overnight electrocardiogram was also recorded with a single lead. Using an MSP430 as microcontroller, both physiological signals were transmitted by a Bluetooth chip. A Labview-based interface demonstrated the recorded signal and sleep posture. Three nights of sleep recordings were used to examine night-to-night variability. The proposed system can record overnight heart rate. Results show that sleep posture and posture change can be precisely detected via tri-axis accelerometer information. There is no significant difference within subject data sets, but there are statistically significant differences among subjects, both for heart rate and for sleep posture distribution. The wireless transmission range is also sufficient for home-based users.

Managing asthma with mobile phones: a feasibility study

Asthma is a chronic disease and a growing health problem worldwide. The objective of this pilot study was to test the feasibility and utilization of tracking asthma symptoms through an innovative mobile phone application. The subjects for this research project consisted of 4 individuals who are currently receiving treatment for asthma from a primary care physician in Ingham County, Michigan. Participants took their peak flow reading each day and used the short message service (SMS) function on their phone and sent it to a Web server. If they did not send it by 11 AM, they received a reminder via an automated SMS to their phone. The resulting data suggest that this method of management is feasible. The data also demonstrate participants' satisfaction in monitoring their asthma in this manner. Using mobile phones for asthma management could improve compliance with asthma action plans and reduce adverse asthma events. Future research could further demonstrate that mobile phones are a new and effective method for providing healthcare.