Niranjan P. Bidargaddi

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Ambulatory electrocardiography is increasingly being used in clinical practice to detect abnormal electrical behavior of the heart during ordinary daily activities. The utility of this monitoring can be improved by deriving respiration, which previously has been based on overnight apnea studies where patients are stationary, or the use of multilead ECG(More)
OBJECTIVES Derive activity and heart rate (HR) monitor-based clinically relevant measures for outpatient cardiac rehabilitation (CR). METHODS We are currently collecting activity/ECG data from patients undergoing cardiac rehabilitation over duration of six weeks. From these data sets, we a) derive various measures which can be used in assessing home-based(More)
Profile hidden Markov models (HMMs) based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile HMM to overcome the limitations of that assumption and to(More)
Major changes in healthcare delivery are needed to ease the pressures caused by global increase in ageing population and prevalence of chronic diseases. Recent care initiatives address these problems by delivering care in community-based settings, away from hospitals. The community care model requires that a patientpsilas health condition is also monitored(More)
The objective is to identify whether it is possible to discriminate between normal and abnormal physiological state based on heart rate (HR), heart rate variability (HRV) and movement activity information in subjects with cardiovascular complications. HR, HRV and movement information were obtained from cardiac patients over a period of 6 weeks using an(More)
Secondary structure, residue contacts and contact numbers play an important role in tertiary structure determination of proteins. In the recent past, mainly due to non local interactions, the Bayesian segmentation approach has been successfully used for secondary structure prediction. In this paper, the performance of the Bayesian segmentation approach has(More)
Profile HMMs based on classical hidden Markov models have been widely applied for alignment and classification of protein sequence families. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile hidden Markov model to overcome the(More)