Wearable monitoring system uses an ultra-low-power application-specific integrated circuit and a beat-to-beat detection algorithm to measure cardiac activity.
Integrated wearable monitoring systems based on body area networks (BANs) enable continuous, reliable, and long-term monitoring of physio- and biological signals on the move, leading to wearable health solutions for next-generation healthcare, wellness, and lifestyle. An electrocardiography (ECG) necklace has been developed to target the simultaneous monitoring of cardiac and physical activity in everyday life situations.
Its unique advantages are a proprietary ultra-low-power application-specific integrated circuit (ASIC) for the acquisition of the ECG signals at very low noise; a proprietary beat-to-beat detection algorithm; and its low power consumption, achieving 7-day autonomy on a small rechargeable battery. Potential applications span from monitoring amateur and top athletes, to chronic diseases monitoring, to post-treatment monitoring for earlier hospital discharge.
Moreover, when ECG sensors are combined with sensors for galvanic skin conductance and respiration (parameters indicating emotion and stress) the system can measure arousal levels. Being able to measure and analyze the emotional state of somebody can be of great value for a variety of applications in the entertainment and medical sector. For example, online avatars can automatically adapt to a player’s state of mind without him having to actively indicate it in a game menu. Or, in drug screening, being able to objectively quantify parameters such as stress can complement the more subjective indication and gradation of traditional tests or questionnaires.
The ECG necklace measures one bipolar ECG lead, and 3-dimensional acceleration. Standard Ag/AgCl electrodes are attached to the body for ECG acquisition. Low-power and high-performance ECG monitoring is achieved through the use of a proprietary single-channel ASIC for biopotential read-out. A proprietary beat detection algorithm runs on the device, and is able to detect the R-peak even under a high level of (motion induced) noise. Its high accuracy in time makes it particularly suitable for heart rate trend and variability analysis. Raw data (ECG and acceleration) and beat-to-beat heart rate can be transmitted wirelessly to a receiving unit, or stored on a secure digital (SD) card.
The ECG necklace achieves one-week autonomy on a 165mAh Li-ion battery, while continuously streaming ECG data. The ECG necklace is being evaluated for ambulatory detection of epileptic seizures overnight, in collaboration with Kempenhaeghe, an expertise center for epilepsy and sleep in the Netherlands. The device detects epileptic seizures based on specific changes in heart rate, and sends an alarm to a computer or mobile phone (Fig. 2). To date, the evaluation of the prototype on eight epileptic patients has shown the potential for ambulatory seizure detection based on heart rate changes. Robust measurements during the day will require additional sensors and advanced signal processing to cope with possible false positives. The technology is also being evaluated for monitoring atrial fibrillation patients before and after pulmonary vein ablation. Patients equipped with the systems are monitored for one month to detect possible atrial fibrillation events.
This technology is also suitable for use with mobile phones. The successful deployment of wearable health systems requires connectivity — connectivity to one’s physician if life critical events are detected, to a call center, to electronic patient records, to one’s relatives in the case of elderly monitoring, to a social community, or simply to one’s personal coach.
The prevalence of mobile phones makes them ideal as a central platform for health monitoring and management. As such, a low-power interface was developed that wirelessly transmits biosignals retrieved by the ECG necklace to an Android mobile phone where the data are collected, stored, processed, and sent over the Internet to make them available to authorized users such as physicians (Fig. 3). The interface is based on a standard Secure Digital Input Output (SDIO) interface on Android mobile phones, enabling the integration of all the features available on Android’s operating system (SMS, e-mail and data transmission over the internet, GPS to track user location). The system allows configuration of thresholds on the measured parameters and automatic sending of alerts such as SMS messages and e-mails based on these values.
This technology was done by imec, Leuven, Belgium. For more information, visit http://info.hotims.com/34455-161.