Biomedical signal processing has become a necessary tool for extracting clinically significant information hidden in physiologic signals. This information can be the physiological state of a patient or even their psychological state in some cases.
The vision of our research is to advance the development of computer based diagnostic and monitoring systems which offer fully automated analysis. These diagnostic systems can help the physician in making well founded decisions and reduce the subjectivity of manual measurements and decision making process. Automated monitoring systems can save life in real-time situations in cases such as apneas and cardiac failures.
The research activity at the Biomedical Signal Processing Research Lab. is concentrate on bioelectrical signals such as the electrocardiograms (ECG) and electroencephalogram (EEG), and physiological acoustic signals such as snore sounds, cough sounds, phonocardiogram (PCG) and voice/speech signals. In these research activities, new methods of signal processing and pattern recognition that extract useful information from the physiological signals are being developed.
Sleep research
Heart research
Smart medical home
Speech research
Sleep evaluation using multi-channel audio signals
Quantification of Autism Symptoms using Speech Signal Processing
COVID-19 diagnosis using cough audio signal processing
The vision of our research is to advance the development of computer based diagnostic and monitoring systems which offer fully automated analysis. These diagnostic systems can help the physician in making well founded decisions and reduce the subjectivity of manual measurements and decision making process. Automated monitoring systems can save life in real-time situations in cases such as apneas and cardiac failures.
The research activity at the Biomedical Signal Processing Research Lab. is concentrate on bioelectrical signals such as the electrocardiograms (ECG) and electroencephalogram (EEG), and physiological acoustic signals such as snore sounds, cough sounds, phonocardiogram (PCG) and voice/speech signals. In these research activities, new methods of signal processing and pattern recognition that extract useful information from the physiological signals are being developed.
Sleep research
- Detection and analysis of breathing and snoring sounds
- Estimation of obstructive sleep apnea (OSA) severity
- Identifying sleep apnea patients from their speech signals
- Estimation of sleep stages from breathing sounds
- Analyzing EEG signals from OSA patients.
Heart research
- Detection of atrial electrical activity in arrhythmias using ECG signals.
- Classification of arrhythmias using ECG signals
Smart medical home
- Fall detection system of elderly using floor vibrations and sound
- Development of a cough detection monitoring device
Speech research
- Age estimation from speech signals
- Robust speaker recognition to reverberant speech
- Room volume estimation from speech signals
Sleep evaluation using multi-channel audio signals
- coping with sleeping partner
- sound and noisy environment
Quantification of Autism Symptoms using Speech Signal Processing
- Immediate echolalia detection.
- Crying and screaming events detection.
- Estimation of autism severity in young children.
COVID-19 diagnosis using cough audio signal processing
- Cough event detection.
- COVID-19 classification.