Arijit Sinharay

Mr. Arijit Sinharay


Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 August 2017 in Sensors
Verified
Journal Article
Open access
PDF file
ASArijit Sinharay
Arijit Sinharay
RRRaj Rakshit
Raj Rakshit
AKAnwesha Khasnobish
Anwesha Khasnobish
TCTapas Chakravarty
Tapas Chakravarty
DGDeb Ghosh
Deb Ghosh
APArpan Pal
Arpan Pal
Pulmonary ailments are conventionally diagnosed by spirometry. The complex forceful breathing maneuver as well as the extreme cost of spirometry renders it unsuitable in many situations. This work is aimed to facilitate an emerging direction of tidal breathing-based pulmonary evaluation by designing a novel, equitable, precise and portable device for acquisition and analysis of directional tidal breathing patterns, in real time. The proposed system primarily uses an in-house designed blow pipe, 40-kHz air-coupled ultrasound transreceivers, and a radio frequency (RF) phase-gain integrated circuit (IC). Moreover, in order to achieve high sensitivity in a cost-effective design philosophy, we have exploited the phase measurement technique, instead of selecting the contemporary time-of-flight (TOF) measurement; since application of the TOF principle in tidal breathing assessments requires sub-micro to nanosecond time resolution. This approach, which depends on accurate phase measurement, contributed to enhanced sensitivity using a simple electronics design. The developed system has been calibrated using a standard 3-L calibration syringe. The parameters of this system are validated against a standard spirometer, with maximum percentage error below 16%. Further, the extracted respiratory parameters related to tidal breathing have been found to be comparable with relevant prior works. The error in detecting respiration rate only is 3.9% compared to manual evaluation. These encouraging insights reveal the definite potential of our tidal breathing pattern (TBP) prototype for measuring tidal breathing parameters in order to extend the reach of affordable healthcare in rural regions and developing areas.

18 May 2020 in IEEE Sensors Journal
Verified
Journal Article
Closed access
DRDibyendu Roy
Dibyendu Roy
ASArijit Sinharay
Arijit Sinharay
BBBrojeshwar Bhowmick
Brojeshwar Bhowmick
RRRaj Rakshit
Raj Rakshit
TCTapas Chakravarty
Tapas Chakravarty
APArpan Pal
Arpan Pal
In this paper, we propose a novel non-contact vibration measurement system that is competent in estimating linear and/or rotational motions of machine parts. The technique combines microwave radar, standard camera, and optical strobe to capture vibrational or rotational motions in a relatively fast and affordable manner when compared to the current technologies. In particular, the proposed technique is capable of not only measuring common vibrational parameters (e.g. frequency, motor rpm, etc.) but also provides spatial information of the vibrational sources so that the origin of each vibrational point can be identified accurately. Furthermore, it can also capture the wobbling motion of the rotating shafts. Thus, the proposed method can find immense applications in preventive maintenance across various industries where heavy machinery needs to be monitored unobtrusively or there is a requirement for non-contact multi-point vibration measurement for any machine inspection applications.

10 December 2022 in Ultrasonics
Verified
Journal Article
Closed access
ASArijit Sinharay
Arijit Sinharay
RRRaj Rakshit
Raj Rakshit
SGSupriya Gain
Supriya Gain
SBSubhadeep Basu
Subhadeep Basu
AKA. Anil Kumar
A. Anil Kumar
TCTapas Chakravarty
Tapas Chakravarty

25 August 2018
Verified
Book Chapter
Closed access
PDF file
DRDibyendu Roy
Dibyendu Roy
PMPrasant Misra
Prasant Misra
TCTapas Chakravarty
Tapas Chakravarty
ASArijit Sinharay
Arijit Sinharay
RRRaj Rakshit
Raj Rakshit
APArpan Pal
Arpan Pal

22 August 2023 in IEEE Sensors Letters
Verified
Journal Article
Closed access
AGAbhijeet Gorey
Abhijeet Gorey
CBChirabrata Bhaumik
Chirabrata Bhaumik
TCTapas Chakravarty
Tapas Chakravarty
AMAnnesha Mazumder
Annesha Mazumder
ASArijit Sinharay
Arijit Sinharay
APArpan Pal
Arpan Pal
Non-destructive and rapid measurement of micro coating thickness is a challenge for most of the paint coating industries. This study proposes a novel sweep frequency photoacoustic sensing technique for the non-destructive estimation of a coating layer thickness. The continuous wave laser diodeused for the sample excitationmakes the overallsystem compact and portable. Also, the usage of frequency sweep enables the technique to be applied to different substrates and different coating layers. The Rosencwaig-Gersho (RG) model is employed to estimate the thickness of the coating layer by measuring the resonance frequency of the photoacoustic wave. Regression analysis is performed to obtain the micro thickness through photoacoustic measurements. The photoacoustic measurements arecompared with the standard (cross-sectional microscopy) thickness measurement technique and the error is found to be less than 5%. The simple computational method and instrumentation used in this technique enable it to be deployed in industries for rapid estimation of the micro thickness.

25 April 2018 in Sensors
Verified
Journal Article
Open access
PDF file
RRRaj Rakshit
Raj Rakshit
AKAnwesha Khasnobish
Anwesha Khasnobish
ACArijit Chowdhury
Arijit Chowdhury
ASArijit Sinharay
Arijit Sinharay
APArpan Pal
Arpan Pal
TCTapas Chakravarty
Tapas Chakravarty
Smoking causes unalterable physiological abnormalities in the pulmonary system. This is emerging as a serious threat worldwide. Unlike spirometry, tidal breathing does not require subjects to undergo forceful breathing maneuvers and is progressing as a new direction towards pulmonary health assessment. The aim of the paper is to evaluate whether tidal breathing signatures can indicate deteriorating adult lung condition in an otherwise healthy person. If successful, such a system can be used as a pre-screening tool for all people before some of them need to undergo a thorough clinical checkup. This work presents a novel systematic approach to identify compromised pulmonary systems in smokers from acquired tidal breathing patterns. Tidal breathing patterns are acquired during restful breathing of adult participants. Thereafter, physiological attributes are extracted from the acquired tidal breathing signals. Finally, a unique classification approach of locally weighted learning with ridge regression (LWL-ridge) is implemented, which handles the subjective variations in tidal breathing data without performing feature normalization. The LWL-ridge classifier recognized compromised pulmonary systems in smokers with an average classification accuracy of 86.17% along with a sensitivity of 80% and a specificity of 92%. The implemented approach outperformed other variants of LWL as well as other standard classifiers and generated comparable results when applied on an external cohort. This end-to-end automated system is suitable for pre-screening people routinely for early detection of lung ailments as a preventive measure in an infrastructure-agnostic way.