Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
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Conf Proc IEEE Eng Med Biol Soc · Jan 2015
Bayesian fusion of algorithms for the robust estimation of respiratory rate from the photoplethysmogram.
Respiratory rate (RR) is a key vital sign that is monitored to assess the health of patients. With the increase of the availability of wearable devices, it is important that RR is extracted in a robust and noninvasive manner from the photoplethysmogram (PPG) acquired from pulse oximeters and similar devices. However, existing methods of noninvasive RR estimation suffer from a lack of robustness, resulting in the fact that they are not used in clinical practice. ⋯ Our proposed methodology resulted in a mean-absolute-error (MAE) of 1.98 breaths per minute (bpm), outperformed other fusing strategies (mean fusion: 2.95 bpm; median fusion: 2.33 bpm; ML: 2.30 bpm). It also outperformed the best single algorithm (2.39 bpm) and the benchmark algorithm proposed for use with Capnobase (2.22 bpm). We conclude that the proposed fusion methodology can be used to combine RR estimates from multiple sources derived from the PPG, to infer a reliable and robust estimation of the respiratory rate in an unsupervised manner.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2015
Sleep stage classification by body movement index and respiratory interval indices using multiple radar sensors.
Disturbed sleep has become more common in recent years. To increase the quality of sleep, undergoing sleep observation has gained interest as an attempt to resolve possible problems. In this paper, we evaluate a non-restrictive and non-contact method for classifying real-time sleep stages and report on its potential applications. ⋯ The accuracy was 79.3% for classification and 71.9% for estimation. This is a novel system for measuring body movements and body-surface movements that are induced by respiration and for measuring high sensitivity pulse waves using multiple radar signals. This method simplifies measurement of sleep stages and may be employed at nursing care facilities or by the general public to increase sleep quality.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2015
Seizure detection using regression tree based feature selection and polynomial SVM classification.
This paper presents a novel patient-specific algorithm for detection of seizures in epileptic patients with low hardware complexity and low power consumption. In the proposed approach, we first compute the spectrogram of the input fragmented EEG signals from three or four electrodes. Each fragmented data clip is one second in duration. ⋯ The algorithm is tested using the intra-cranial EEG (iEEG) from the UPenn and Mayo Clinic's Seizure Detection Challenge database. It is shown that the proposed algorithm can achieve a sensitivity of 100.0%, an average area under curve (AUC) of 0.9818, a mean detection horizon of 5.8 seconds, and a specificity of 99.9% on using half of the training data for classification. The proposed approach also achieved a mean AUC of seizure detection and early seizure detection of 0.9136 on the testing data.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2015
Quantitative EEG markers in severe post-resuscitation brain injury with therapeutic hypothermia.
Therapeutic hypothermia has been regarded as one of the most effective post-cardiac arrest (CA) treatments to improve survival and functional recovery. However, many clinical prognostic markers after resuscitation have become less reliable under hypothermia. In this study, we applied and compared two developed quantitative measures - information quantity (IQ) and sub-band IQ (SIQ) - to evaluate the accuracy of EEG markers on predicting cortical recovery under therapeutic hypothermia. ⋯ Contrary to IQ recovery but similarly to NDS scores, the SIQ recovery was not significantly different between the hypothermia (0.66±0.04) and normothermia (0.64±0.04) groups (p>0.05). IQ could identify the presence of high-frequency oscillations during the recovery from severe brain injury. We demonstrated that while SIQ was able to provide additional sub-band EEG information related to the recovery of different brain functions, both early IQ and SIQ markers are able to accurately predict neurologic outcome after CA.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
A portable multi-channel wireless NIRS device for muscle activity real-time monitoring.
Near-infrared spectroscopy (NIRS) is a relative new technology in monitoring muscle oxygenation and hemo-dynamics. This paper presents a portable multi-channel wireless NIRS device for real-time monitoring of muscle activity. The NIRS sensor is designed miniaturized and modularized, to make multi-site monitoring convenient. ⋯ Besides, the system is designed with high sampling rate so as to monitor rapid oxygenation changes during muscle activities. Dark noise and long-term drift tests have been carried out, and the result indicates the device has a good performance of accuracy and stability. In vivo experiments including arterial occlusion and isometric voluntary forearm muscle contraction were performed, demonstrating the system has the ability to monitor muscle oxygenation parameters effectively even in exercise.