Variations in fetal heart rate (FHR) is a potential indicator of stress on unborn in the womb of mother. In hospitals, FHR surveillance is performed by ultrasound based Doppler equip-ments. However, recent studies sho...Variations in fetal heart rate (FHR) is a potential indicator of stress on unborn in the womb of mother. In hospitals, FHR surveillance is performed by ultrasound based Doppler equip-ments. However, recent studies show that frequent exposure to ultrasound radiations is not recommended for the fetal well-being. Because of this and many other reasons, these instruments are not recommended for prolonged home monitoring applications. This work is focused around development of a prototype system for fetal home monitoring application. Presented system can record the abnormal FHR and alert the pregnant women to report to a physician. Recorded data is then processed by a novel methodology for deriving results of diagnostic importance. The instrument has been tested on pregnant women in the clinical environment and has gone through an extensive clinical trial at local hospitals. The results show that the technique is suitable and effective for long-term FHR home monitoring application.展开更多
Phonocardiogram （PCG）, the digital recording of heart sounds is becoming increasingly popular as a primary detection system for diagnosing heart disorders and it is relatively inexpensive. Electrocardiogram （ECG） ...Phonocardiogram （PCG）, the digital recording of heart sounds is becoming increasingly popular as a primary detection system for diagnosing heart disorders and it is relatively inexpensive. Electrocardiogram （ECG） is used during the PCG in order to identify the systolic and diastolic parts manually. In this study a heart sound segmentation algorithm has been developed which separates the heart sound signal into these parts automa- tically. This study was carried out on 100 patients with normal and abnormal heart sounds. The algorithm uses discrete wavelet decomposition and reconstruction to pro- duce PCG intensity envelopes and separates that into four parts： the first heart sound, the systolic period, the second heart sound and the diastolic period. The performance of the algorithm has been evaluated using 14,000 cardiac periods from 100 digital PCG recordings, including normal and abnormal heart sounds. In tests, the algorithm was over93% correct in detecting the first and second heart sounds. The presented automatic seg- mentation Mgorithm using w^velet decomposition and reconstruction to select suitable frequency band for envelope calculations has been found to be effective to segment PCG signals into four parts without using an ECG.展开更多
文摘Variations in fetal heart rate (FHR) is a potential indicator of stress on unborn in the womb of mother. In hospitals, FHR surveillance is performed by ultrasound based Doppler equip-ments. However, recent studies show that frequent exposure to ultrasound radiations is not recommended for the fetal well-being. Because of this and many other reasons, these instruments are not recommended for prolonged home monitoring applications. This work is focused around development of a prototype system for fetal home monitoring application. Presented system can record the abnormal FHR and alert the pregnant women to report to a physician. Recorded data is then processed by a novel methodology for deriving results of diagnostic importance. The instrument has been tested on pregnant women in the clinical environment and has gone through an extensive clinical trial at local hospitals. The results show that the technique is suitable and effective for long-term FHR home monitoring application.
文摘Phonocardiogram （PCG）, the digital recording of heart sounds is becoming increasingly popular as a primary detection system for diagnosing heart disorders and it is relatively inexpensive. Electrocardiogram （ECG） is used during the PCG in order to identify the systolic and diastolic parts manually. In this study a heart sound segmentation algorithm has been developed which separates the heart sound signal into these parts automa- tically. This study was carried out on 100 patients with normal and abnormal heart sounds. The algorithm uses discrete wavelet decomposition and reconstruction to pro- duce PCG intensity envelopes and separates that into four parts： the first heart sound, the systolic period, the second heart sound and the diastolic period. The performance of the algorithm has been evaluated using 14,000 cardiac periods from 100 digital PCG recordings, including normal and abnormal heart sounds. In tests, the algorithm was over93% correct in detecting the first and second heart sounds. The presented automatic seg- mentation Mgorithm using w^velet decomposition and reconstruction to select suitable frequency band for envelope calculations has been found to be effective to segment PCG signals into four parts without using an ECG.
