Division of Healthcare Advancement, Innovation and Research

The multidisciplinary division for Healthcare Advancement, Innovation and  Research aims in bringing a fresh perspective to the challenges of embedding health and social care innovations, sustainability at large.  We, actively, encompass to be at the forefront of cutting-edge advancements in teaching, training & research by setting an example in preserving lives & providing all technological solutions under one roof at an affordable cost. We bring together experts from a variety of disciplines across, including electronics engineers, bioengineers, computer scientists, chemists, healthcare Professionals and clinicians. Some of the thrust areas include bio-signals/bio-imaging, speech signal, developing biosensors, wearable technology, eHealth & telemedicine, non-invasive medical devices, rehabilitative and assistive device technology, BCI applications, biomechanics, biorobotics, bioinformatics, clinical support/data management system and also on developing computer-aided affordable diagnostic tools through technological intervention.

The key emphasis of research Centre is:

  • To strengthen innovation and technology in healthcare by focusing on signal and image processing solutions using artificial intelligence concepts, with prime focus on machine learning and deep learning technology.
  • To bridge the gap between healthcare sciences and technology transformation by developing innovative products.
  • To develop low-cost flexible novel 2D-nanomaterial-based biosensors with high sensitivity and theranostic agents for cancer imaging and targeting.
  • innovative product development
  • to prominently engage in impending application areas such as smart health care, smart merchandise, smart agriculture, etc., and foster economical solutions


1 Speed of Sound based Capnographic Sensor using Virial Equation


201841015926 A





Development of a Non-Invasive Detection and Classification System of five Types of Diabetes Through Breath


201841015927 A 04/05/2018




3 Method And Apparatus For Non-Invasive Detection of Chronic Kidney Disease by Monitoring Saliva Urea 201841012758 A 11/05/2018




4 Method And Apparatus for Non-Invasive Detection of Five Types of Diabetes and Classification by Monitoring Sweat Concentration 201841033749 A 2/11/2018


Mr. Sankar Narayanan



S.No Title Funding  Agency Amount Investigators Duration
1. MST Radar Signal Processing using Variational Mode Decomposition based Adaptive Structures

Indian Space Research Organisation







2 Development of automated classification algorithm for studying cognitive behaviour from Scalp EEG signals SEED Grant Rs.3,00,000/- Dr.M.Suchetha




  1. NavaneethBhaskar., M.Suchetha., “Time Series Classification based Correlational Neural Network with Bidirectional LSTM for Automated Detection of Kidney Disease”., IEEE SENSORS Journal, 2020 (Accepted for publication) [IF: 3.076]
  2. S.Lekha.,M.Suchetha.,“Recent Advancements and Future Prospects on E-Nose Sensors Technology and Machine Learning Approaches for Non- Invasive Diabetes Diagnosis: A Review”, IEEE Reviews in Biomedical Engineering,2020 (DOI: 10.1109/RBME.2020.2993591)[IF: 6.85]
  3. Navaneeth., M.Suchetha., “A Dynamic Pooling based Convolutional Neural Network Approach to Detect Chronic Kidney Disease” Journal of Biomedical Signal processing and control, Vol.62, Sep 2020 (https://doi.org/10.1016/j.bspc.2020.102068) [IF: 3.341]
  4. V. Athanasiou, K. K. Tadi, M. Hurevich, S. Yitzchaik, A. Jesorka, Z. Kankoli, “On sensing principles using temporally extended bar codes”,IEEE Sensors, 2020, 20, 6782-2791  [IF-3.078]
  5. Joseph Antony., M.Suchetha., “Expanding vision-based ADAS for non- structured environments” IET Intelligent Transport Systems.,vol.14,Issue:6, 2020 [IF: 2.95]
Faculty Book Title/Chapter Name ISBN no. year Publisher
Sangeetha N, Anita X and Vijayarajan R Medical Image Watermarking: A Review on Wavelet-Based Methods, Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems 978-981-15-6140-5 2020

https://doi.org/ 10.1007/978-981-15-6141-2_11


Springer Nature. 2020

Alex, John Sahaya Rani; Kumar, M Abai; Swathy, DV; Deep Learning Approaches for Fall Detection Using Acoustic Information, Advances in Smart Grid Technology 978-981-15-7241-8 2020


Springer Nature. 2020


Research Scholars working in Centre

Mr. Navaneeth Bhaskar, Ms. Bhagya D, Mr. Satheesh Kumar reddy C, Mr. Ranjith Kumar P, Ms. Smruthy A, Mr. Joseph Antony J, Ms. Nasheeda V P, Mr. Kantharao Kancharla, Mrs. Kavitha Rani T, Mr. R. Manikandan, Mr.  S. Sam Baskar Bagavathsingh, Ms. Gowri Prasood U and Mr.Edwin Dhas D




S.No. Award Faculty Agency Year
1. Reviewer Recognition Dr.R.Vijayarajan Elsevier (Biomedical signal processing and control) 2020
2. Reviewer Recognition Dr. Kiran Kumar Tadi Sens. Act. B/Elsevier 2020
3. Reviewer Recognition Dr. Kiran Kumar Tadi Journal of Fluorine Chemistry/Elsevier 2020


S.No. Award Faculty Agency Year
1. Appreciation award Dr.John Sahaya Rani Alex IEEE SPS 2019

IEEE Publication Award

(4 medals for 4 papers)

Dr.M.Suchetha IEEE Madras 2019


S.No. Award Faculty Agency Year
1. Young Researcher Award-  Republic day Achievers Award Dr.M.Suchetha Intelligent Research India 2018
2. Fellowship Dr.R.Vijayarajan IETE 2018


S.No. Award Faculty Agency Year
1. Reviewer Recognition Dr. Gargi Raina Nature Publishing Group 2017
2. Outstanding Professional award – Women Achievers Dr.M.Suchetha FICCI-FLO 2017
3. Chemosensors Travel Award Dr. Kiran Kumar Tadi MDPI Publishers 2017
4. The Arskin Postdoctoral Fellowship Dr. Kiran Kumar Tadi The Hebrew University of Jerusalem, Israel 2017



Diabetes detection from breath (Faculty: Dr.M.Suchetha &  Research Scholar: S.Lekha)

Chronic kidney disease detection from saliva(Faculty: Dr.M.Suchetha & Research Scholar: Navaneeth Bhaskar)

Cardiorespiratory Abnormalities from breath (Faculty: Dr.M.Suchetha & Research Scholar: D.Bhagya)

Cardiorespiratory Abnormalities from breath (Faculty: Dr.M.Suchetha & Research Scholar: D.Bhagya)

Harnessing the 2-dimensional material, Fluorinated graphene for the fabrication of highly sensitive, selective and fast responsive ammonia sensor (Faculty: Kiran Kumar Tadi)