11 accepted papers
In recent times, plasmonic sensing is widely used for detecting tiny particles (micro / nano-scale) and plays a crucial role in diverse application domains such as sustainability, healthcare etc. In current scenario, numerical simulators are used for predicting the optical response of a plasmonic na…
The growing use of wearable devices requires accurate and compact representations of high dimensional physiological signals. This work presents a UNet inspired autoencoder to represent and reconstruct multiple neuro-physiological signals from single channel data. The architecture comprises single-en…
Construction of learning model under computational and energy constraints, particularly in highly limited training time requirement is a critical as well as unique necessity of many practical IoT applications that use time series sensor signal analytics for edge devices. Yet, majority of the state-o…
Automatic Carnatic Music (CM) transcription is an open problem in need of a standardized descriptive notation. The level of detail needed in a descriptive transcription makes it tedious to obtain ground truth by manual means. In this paper, we propose a novel state-based representation of the pitch…
A robot as a coworker or a cohabitant is becoming mainstream day-by-day with the development of low-cost sophisticated hardware. However, an accompanying software stack that can aid the usability of the robotic hardware remains the bottleneck of the process, especially if the robot is not dedicated…
In this paper, we present completely automated cardiac anomaly detection for remote screening of cardio-vascular abnormality using Phonocardiogram (PCG) or heart sound signal. Even though PCG contains significant and vital cardiac health information and cardiac abnormality signature, the presence of…
Remote cardiac health management is an important healthcare application. We have developed Heartmate that enables basic screening of cardiac health using low cost sensors or smartphone-inbuilt sensors without manual intervention. It consists of robust denoising algorithm along with effective anomaly…
This paper presents a demo proposal of a standalone smartphone application that can automatically analyse the signal quality of PCG, as it is recorded on a low-cost smartphone-based digital stethoscope. Features, related to the inherent pattern of the autocorrelated signal envelope, have been used f…
In this paper we leverage the power of smartphone to enable proactive in-house heart condition monitoring. We introduce Heart-Trend, a nonparametric model to analyze and detect heart abnormality conditions like arrhythmia from photoplethysmogram (PPG) signal. It does on-demand heart status monitorin…
Sensor nodes are embodiment of IoT systems in microscopic level. As the volume of sensor data increases exponentially, data compression is essential for storage, transmission and in-network processing. The compression performance to realize significant gain in processing high volume sensor data cann…
Photoplethysmography (PPG) signals, captured using smart phones are generally noisy in nature. Although they have been successfully used to determine heart rate from frequency domain analysis, further indirect markers like blood pressure (BP) require time domain analysis for which the signal needs t…