The Experts below are selected from a list of 12 Experts worldwide ranked by ideXlab platform
Kwang Suk Park - One of the best experts on this subject based on the ideXlab platform.
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automatic noise removal and peak detection algorithm for ecg measured from capacitively coupled electrodes included within a cloth Mattress Pad
Journal of Biomedical Engineering Research, 2014Co-Authors: Hee Nam Yoon, Gih Sung Chung, Kwang Suk ParkAbstract:Abstract: Recent technological advances have increased interest in personal health monitoring. Electrocardio-gram(ECG) monitoring is a basic healthcare activity and can provide decisive information regarding cardiovascularsystem status. In this study, we developed a capacitive ECG measurement system that can be included within a clothMattress Pad. The device permits ECG data to be obtained during sleep by using capacitive electrodes. However,it is difficult to detect R-wave peaks automatically because signals obtained from the system can include a high levelof noise from various sources. Because R-peak detection is important in ECG applications, we developed an algorithmthat can reduce noise and improve detection accuracy under noisy conditions. Algorithm reliability was evaluated bydetermining its sensitivity(Se), positive predictivity(+P), and error rate(Er) by using data from the MIT-BIH Poly-somnographic Database and from our capacitive ECG system. The results showed that Se = 99.75%, +P = 99.77%,and Er = 0.47% for MIT-BIH Polysomnographic Database while Se = 96.47%, +P = 99.32%, and Er = 4.34% forour capacitive ECG system. Based on those results, we conclude that our R-peak detection method is capable of pro-viding useful ECG information, even under noisy signal conditions.Key words: Capacitively Measured ECG, R-peak Detection, Ubiquitous Healthcare, Non-intrusive ECG MonitoringSystem, MIT-BIH Polysomnographic Database
Hee Nam Yoon - One of the best experts on this subject based on the ideXlab platform.
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automatic noise removal and peak detection algorithm for ecg measured from capacitively coupled electrodes included within a cloth Mattress Pad
Journal of Biomedical Engineering Research, 2014Co-Authors: Hee Nam Yoon, Gih Sung Chung, Kwang Suk ParkAbstract:Abstract: Recent technological advances have increased interest in personal health monitoring. Electrocardio-gram(ECG) monitoring is a basic healthcare activity and can provide decisive information regarding cardiovascularsystem status. In this study, we developed a capacitive ECG measurement system that can be included within a clothMattress Pad. The device permits ECG data to be obtained during sleep by using capacitive electrodes. However,it is difficult to detect R-wave peaks automatically because signals obtained from the system can include a high levelof noise from various sources. Because R-peak detection is important in ECG applications, we developed an algorithmthat can reduce noise and improve detection accuracy under noisy conditions. Algorithm reliability was evaluated bydetermining its sensitivity(Se), positive predictivity(+P), and error rate(Er) by using data from the MIT-BIH Poly-somnographic Database and from our capacitive ECG system. The results showed that Se = 99.75%, +P = 99.77%,and Er = 0.47% for MIT-BIH Polysomnographic Database while Se = 96.47%, +P = 99.32%, and Er = 4.34% forour capacitive ECG system. Based on those results, we conclude that our R-peak detection method is capable of pro-viding useful ECG information, even under noisy signal conditions.Key words: Capacitively Measured ECG, R-peak Detection, Ubiquitous Healthcare, Non-intrusive ECG MonitoringSystem, MIT-BIH Polysomnographic Database
Gih Sung Chung - One of the best experts on this subject based on the ideXlab platform.
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automatic noise removal and peak detection algorithm for ecg measured from capacitively coupled electrodes included within a cloth Mattress Pad
Journal of Biomedical Engineering Research, 2014Co-Authors: Hee Nam Yoon, Gih Sung Chung, Kwang Suk ParkAbstract:Abstract: Recent technological advances have increased interest in personal health monitoring. Electrocardio-gram(ECG) monitoring is a basic healthcare activity and can provide decisive information regarding cardiovascularsystem status. In this study, we developed a capacitive ECG measurement system that can be included within a clothMattress Pad. The device permits ECG data to be obtained during sleep by using capacitive electrodes. However,it is difficult to detect R-wave peaks automatically because signals obtained from the system can include a high levelof noise from various sources. Because R-peak detection is important in ECG applications, we developed an algorithmthat can reduce noise and improve detection accuracy under noisy conditions. Algorithm reliability was evaluated bydetermining its sensitivity(Se), positive predictivity(+P), and error rate(Er) by using data from the MIT-BIH Poly-somnographic Database and from our capacitive ECG system. The results showed that Se = 99.75%, +P = 99.77%,and Er = 0.47% for MIT-BIH Polysomnographic Database while Se = 96.47%, +P = 99.32%, and Er = 4.34% forour capacitive ECG system. Based on those results, we conclude that our R-peak detection method is capable of pro-viding useful ECG information, even under noisy signal conditions.Key words: Capacitively Measured ECG, R-peak Detection, Ubiquitous Healthcare, Non-intrusive ECG MonitoringSystem, MIT-BIH Polysomnographic Database
Nino Ullrich - One of the best experts on this subject based on the ideXlab platform.
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Development of Sensate and Robotic Bed Technologies for Vital Signs Monitoring and Sleep Quality Improvement
2014Co-Authors: H. F. Machiel, Van Der Loos, Nino UllrichAbstract:Abstract. More than 50 million people in the U.S. suffer from chronic sleep disorders, including snoring, bruxism, restless legs syndrome, and obstructive sleep apnea. Clinical diagnosis of severe cases often requires expensive, hospital-based polysomnography testing, while less severe cases may benefit from lower-cost in-home sensor systems to collect physiological data over multiple nights. Remedies for sleep disorders, depending on the diagnosis, range from life style modification and medication prescription to throat surgery. There is a need for unobtrusive, in-bed sensing systems as well as robotic devices to alleviate certain sleep disorder symptoms. Two companion devices are presented. The SleepSmart device is a multi-sensor Mattress Pad controlled by software to detect heart rate, breathing rate, body orientation and index of restlessness. A spectral analysis module is combined with an event detection module to accumulate nightly reports, signal alarms when appropriate and, in future iterations, modify ambient conditions in the bedroom. A companion project has developed Morpheus, a Mattress actuation system to encourage a person to roll over in bed to alleviate snoring based on acoustic sensor data analysis. The combination of the two systems is expected to lead to novel, in-home consumer devices to aid persons affected by mild forms of sleep disorders. Keywords: sleep research, sleep apnea, vital signs monitoring, robot be
H. F. Machiel - One of the best experts on this subject based on the ideXlab platform.
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Development of Sensate and Robotic Bed Technologies for Vital Signs Monitoring and Sleep Quality Improvement
2014Co-Authors: H. F. Machiel, Van Der Loos, Nino UllrichAbstract:Abstract. More than 50 million people in the U.S. suffer from chronic sleep disorders, including snoring, bruxism, restless legs syndrome, and obstructive sleep apnea. Clinical diagnosis of severe cases often requires expensive, hospital-based polysomnography testing, while less severe cases may benefit from lower-cost in-home sensor systems to collect physiological data over multiple nights. Remedies for sleep disorders, depending on the diagnosis, range from life style modification and medication prescription to throat surgery. There is a need for unobtrusive, in-bed sensing systems as well as robotic devices to alleviate certain sleep disorder symptoms. Two companion devices are presented. The SleepSmart device is a multi-sensor Mattress Pad controlled by software to detect heart rate, breathing rate, body orientation and index of restlessness. A spectral analysis module is combined with an event detection module to accumulate nightly reports, signal alarms when appropriate and, in future iterations, modify ambient conditions in the bedroom. A companion project has developed Morpheus, a Mattress actuation system to encourage a person to roll over in bed to alleviate snoring based on acoustic sensor data analysis. The combination of the two systems is expected to lead to novel, in-home consumer devices to aid persons affected by mild forms of sleep disorders. Keywords: sleep research, sleep apnea, vital signs monitoring, robot be