Robust Audio and WiFi Sensing via Domain Adaptation and Knowledge Sharing From External Domains

Recent advancements in machine learning have initiated a revolution in embedded sensing and inference systems. Acoustic and WiFi-based sensing and inference systems have enabled a wide variety of applications ranging from home activity detection to health vitals monitoring. While many existing solutions paved the way for acoustic event recognition and WiFi-based activity detection, the diverse characteristics in sensors, systems, and environments used for data capture cause a shift in the distribution of data and thus results in sub-optimal classification performance when the sensor and environment discrepancy occurs between training and inference stage. Moreover, large-scale acoustic and WiFi data collection is non-trivial and cumbersome. Therefore, current acoustic and WiFi-based sensing systems suffer when there is a lack of labeled samples as they only rely on the provided training data. In this thesis, we aim to address the performance loss of machine learning-based classifiers for acoustic and WiFi-based sensing systems due to sensor and environment heterogeneity and lack of labeled examples. We show that discovering latent domains (sensor type, environment, etc.) and removing domain bias from machine learning classifiers make acoustic and WiFi-based sensing robust and generalized. We also propose a few-shot domain adaptation method that requires only one labeled sample for a new domain that relieves the users and developers from the painstaking task of data collection at each new domain. Furthermore, to address the lack of labeled examples, we propose to exploit the information or learned knowledge from sources where available data already exists in volumes, such as textual descriptions and visual domain. We implemented our algorithms in mobile and embedded platforms and collected data from participants to evaluate our proposed algorithms and frameworks in an extensive manner.Doctor of Philosoph

A clinical study of arrhythmias associated with acute coronary syndrome: a hospital based study of a high risk and previously undocumented population

Background: ACS represents a global epidemic. Arrhythmia in ACS is common. Careful investigation may lead to further improvement of prognosis. Retrospectively analyzed the year- round data of our center. Study was undertaken to analyze the incidence, frequency and type of arrhythmias in ACS. This is to aid timely intervention and to modify the outcome. Identification of the type of arrhythmia is of therapeutic and prognostic importance.Methods: This cross sectional analytical study was conducted in the Department of Cardiology, Apollo Hospitals Dhaka, from January 2019 to January 2020 with ACS patients. Enrolled consecutively and data analyzed.Results: There were 500 patients enrolled considering inclusion and exclusion criteria. Sample was subdivided into 3 groups on the type of ACS. Group-I with UA, Group-II with NSTE - ACS and Group-III with STE - ACS. Different types of arrhythmia noted. Types of arrhythmia were correlated with type of ACS. 500 patients included. Mean age 55.53±12.70, 71.6% male and 28.4% female. 60.4% hypertensive, 46.2% diabetic, 20.2% positive family history of CAD, 32.2% current smoker, 56.4% dyslipidaemic and 9.6% asthmatic. 31.2% UA, 39.2% NSTE-ACS and 29.6% STE-ACS. Type of arrhythmias noted. 22% sinus tachycardia, 20.2% sinus bradycardia, 9% atrial fibrillation, 5.2% ventricular ectopic, 4.8% supra ventricular ectopic, 2.8% bundle branch block, 2.2% atrio-ventricular block, 1% broad complex tachycardia, 0.4% narrow complex tachycardia, 0.2% sinus node dysfunction and 32.2% without any arrhythmia. Significant incidences of arrhythmia detected - respectively 29.8%, 39.2% and 31%, p<0.001.Conclusions: In conclusion, arrhythmias in ACS are common. More attention should be paid to improve their treatment and prognosis

An 8-year-old boy with renal artery stenosis and cerebral infarct

Secondary hypertension is more common in children compared to that in adults, leading to organ damage and increased mortality. Renal artery stenosis could be a sequel to secondary hypertension in children and give rise to serious outcomes. A case of renal artery stenosis in an eight year old boy is presented in this study in whom PTA was performed with successful results. Blood pressure was controlled and all antihypertensive drugs could be withdrawn in a short period of time. Ibrahim Med. Coll. J. 2011; 5(1): 32-3