K. A. Unnikrishna Menon currently serves as Visiting Professor at Amrita Center for Wireless Networks and Applications (AmritaWNA). His areas of interest include Electro- Acoustic Sensor Design, Development and Evaluation, SONAR Antenna Design & Field Implementation, Sensor for Under Water Communication, Research and Development in Underwater Transducer Design, Project Management, Techno Mechanical activities.
Qualification: PG in Physics with Electronics as special subject.
Occupation / Post Held: Retd. Scientist-F / Jt.Director (Division-Head "Transducer design and Measurements”, Defence Research & Development Organization (DRDO, Ministry of Defence)
Present Work: Professor, Amrita Center for Wireless Network and Applications, Amrita Viswa Vidyapeetham, Amritapuri, Clappana P.O., Kollam-690525, Kerala.
Experience: Teaching: Seven years at graduate level.
Research: Thirty years experience in the field of development of Underwater Electro- acoustic Transducers for various Sonar Systems of the Indian Navy for induction to ships, submarines and airborne operations. Development of sensors for Tsunami Warning system and Life Recovery System during earthquake.
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2018 |
A. Luke, Shereena Shaji, and K. A. Unnikrishna Menon, “Motion Artifact Removal and Feature Extraction from PPG Signals Using Efficient Signal Processing Algorithms”, in 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2018.[Abstract] The performance of wearable Photoplethysmographic Biosensors can be highly influenced by the motion artifacts. This work proposes a performance enhancement algorithm which can remove the effect of motion artifacts caused by the voluntary movements during various physical activities of an individual. We have developed and implemented three motion artifact removal algorithms namely, ICA-Adaptive Filter Algorithm, Butterworth-ICA-Adaptive Filter Algorithm and Butterworth-Wavelet Transform Algorithm. These three algorithms were analyzed under four fingertip movements like vertical movement, horizontal movement, shivering, and applying pressure. Based on the analysis we found that the Butterworth-Wavelet Transform Algorithm is better in providing high Signal to Noise Ratio (SNR) without compromising any signal characteristics and the algorithm validation was done by extracting Heart Rate (HR) and Peripheral Oxygen Saturation (SpO2) values using Photoplethysmographic (PPG) signals obtained from available Biosensor. The results are found promising and suggest that the Butterworth-Wavelet Transform Algorithm provides motion artifact-free PPG signal for accurate feature extraction. More »» |
2018 |
D. Arjun, Indukala, P. K., and K. A. Unnikrishna Menon, “Border surveillance and intruder detection using wireless sensor networks: A brief survey”, in 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2018.[Abstract] Intrusion of terrorists and trespassers are adversely affecting the peace and harmony in the nation. The fatalities and disturbances caused by the latest Uri attack in Indian Army Camp show the necessity of an efficient border surveillance and intruder detection system for the effective monitoring and detecting the unauthorized movement of intruders across the national borders. Conventional border patrolling lacks an integrated multi-sensing system that coordinates various technologies for surveillance and detection of human intruder movement in the different border scenarios: flat surface movement, river/pond crossing and dry leaves movement. This paper describes the current Wireless Sensor Network (WSN) techniques related to intruder detection and border surveillance. Our future work focuses on delivering an improved multi-sensing system for detecting intrusion activities to secure the national borders. More »» |
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2018 |
K. A. Unnikrishna Menon, Jayaram, R., and Divya, P., “Wearable Wireless Tongue Controlled Devices ”, 2018. |
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2018 |
Gayathri B, K., S., and K. A. Unnikrishna Menon, “Non-Invasive Blood Glucose Monitoring using Near Infrared Spectroscopy”, 6th International Conference on Communication & Signal Processing, ICCSP 2017. IEEE, Chennai, India, 2018.[Abstract] Diabetes has become a grave concern which can affect anyone irrespective of their age. To prevent the uneasiness of invasive glucose monitoring system, it is desirable to develop a low cost non-invasive blood glucose monitoring system. The present work proposes the feasibility of developing such a method for the continuous monitoring of blood glucose concentration using near infrared spectroscopy. Both linear regression and polynomial regression analysis are studied for developing an enhanced algorithm for estimation of glucose concentration using the scattering property of glucose molecules and the principle of photoplethysmography. Processing of data conversion is performed with MSP430G2553 microcontroller in the integrated development environment (IDE) of Code Composer Studio (CCS). Data analysis is carried out in MATLAB from which a relation between blood glucose concentration and photoplethysmograph is derived. More »» |