A system for assessing motion artifacts in the signal of a micro-optic in-ear vital signs sensor.

Cardiovascular diseases are among the most common causes of death in developed industrial nations. It is of great interest of both physician and patient to determine the cardiovascular risk factors early in order to take preventive measures. To assist these investigations we develop a wearable in-ear measuring system (IN-MONIT) for 24/7 monitoring of heart rate and oxygen saturation (SpO2). The central component is a micro-optic remission/reflection sensor (MORES) located inside the auditory canal. From the measured photoplethysmographic curves the aforementioned vital signs can be derived. In the following we present a recording system for assessing motion artifact influence in the in-ear sensor data. Two accelerometer sensors record posture and motion while at the same time SpO2, heart rate and PPG are measured using both a commercial sensor and the in-ear sensor. The data is transmitted wirelessly to a control PC for storage and further investigation. Using this system we assessed the influence of motion artifacts produced by daily life activities on infrared and red in-ear PPG data and on readings of the reference sensor.

In-ear heart rate monitoring using a micro-optic reflective sensor.

Cardiovascular diseases are among the most common causes of death in western industrial nations. It is of great interest of both physician and patient to determine the cardiovascular risk factors early in order to take preventive measures. To assist the recognition of irregularities in a subject's cardiovascular system, we develop an optic 24/7 inear monitoring system (IN-MONIT). The central component is a micro-optic remission/reflection sensor (MORES), which is placed inside the auditory canal. There the pulsation of blood within the capillaries is measured by means of optical absorption. From the resulting photoplethysmographic curves (pulse plethysmogram, PPG), the heart rate, oxygen saturation (SpO2), respiratory rate and higher order moments can be derived. The optical absorption data are processed locally using a microcontroller and the results are transferred wirelessly to a personal digital assistant (PDA) or PC for sophisticated classification. This paper introduces the IN-MONIT system and two algorithms for heart rate determination from ECG or PPG data. The performance of these algorithms was tested using annotated ECG data from the "MIT-BIH Normal Sinus Rhythm Database", synchronously recorded ECG and pulse oximeter data, and data acquired by the MORES sensor.