Dr Om Prakash Singh

1. Om Prakash Singh, Yuan Hu, Frank Stam Andrea Bocchino, Theo Guillerm, Conor O'Mahony,” Flexible, Conductive Fabric‐Backed, Microneedle Electrodes for Electrophysiological Monitoring. Advanced Materials Technologies. 2023 Dec 9:2301606.
2. El-Badawy, Ismail M., Zaid Omar, and Om Prakash Singh, "An effective machine learning approach for classifying artefact-free and distorted capnogram segments using simple time-domain features." IEEE Access (2022). Web of Science (IF – 3.367).
3. Om Prakash Singh, Marta Vallejo, Ismail M. El-Badawy, Ali Aysha, Jagannathan Madhanagopal, and Ahmad Athif Mohd Faudzi "Classification of SARS-CoV-2 and non-SARS-CoV-2 using machine learning algorithms." Computers in biology and medicine 136 (2021): 104650. Web of Science (IF – 4.589, Q1).
4. Om Prakash Singh, Ismail M. El-Badawy, and M. B. Malarvili. "Design and validation of a handheld capnography device for cardiopulmonary assessment based on the Arduino platform." Journal of Innovative Optical Health Sciences 14.6 (2021): 2150015. Web of Science (IF – 1.77).
5. Chia, Kau Pui, Ooi Ke Li, Teh Shyong Yuong, Om Prakash Singh, Ahmad Athif Bin Mohd Faudzi, Sundaram Sornambikai, and Jagannathan Madhanagopal. "New real-time force monitoring device with enhanced accuracy for evaluation of applied force during the joint mobilization technique." Technology and Health Care Preprint (2021): 1-8. Web of Science (IF – 1.285).
6. Ismail M. El-Badawy, Om Prakash Singh, and Z Omar,” Automatic classification of regular and irregular capnogram segments using time-and frequency-domain features: A machine learning-based approach”, Technology and Health Care, Preprint (2020): 1-14., Web of Science, (IF-0.806, Q4).
7. Om Prakash Singh, Teo Aik Howe, MB Malarvili, “Real time human respiration carbon dioxide measurement device for cardiorespiratory assessment”, Journal of Breath Research, Volume 12, 2018-Issue 2. Web of Science (IF – 4.318, Q1).
8. Om Prakash Singh, Ramaswamy Palaniappan and MB Malarvili, “Automatic Quantitative Analysis of Human Respired Carbon Dioxide Waveform for Asthma and Non-Asthma Classification Using Support Vector Machine”, IEEE Access, Vol. 6 (2018). Web of Science (IF – 3.577, Q1).
9. Om Prakash Singh, Ismail Bin Ahmed, MB Malarvili, ” Assessment of Newly Developed Real-Time Human Respiration Carbon Dioxide Measurement Device for Management of Asthma outside of hospital”, Technology and Health Care, Vol. 26, No.5, Web of Science (IF-0.724, Q4).
10.Om Prakash Singh, Ismail M. El-Badawy, M.B. Malarvili, “Development of handheld capnography device using open-source electronic platform Arduino for cardiopulmonary evaluation”, IETE Journal of Research, Under Review, Web of Science (IF – 0.818, Q4).
11. Om Prakash Singh, M.B. Malarvili, “Review of Infrared Carbon-Dioxide Sensor and capnogram features for Developing an Asthma-Monitoring Device”, in Journal of Clinical and Diagnostic Research, Volume 12, Issue 10, pp. OE01-OE06, Scopus & Emerging Sources Citation Index (Web of Science).
12. Om Prakash Singh, Dawit Mekonnen, and M.B. Malarvili “Labview Based ECG Patient Monitoring System for Cardiovascular Patient Using SMTP Technology”, Hindawi Publishing Corporation, Journal of Medical Engineering, Volume 2015, Article ID 701520,9 pages, http://dx.doi.org/10.1155/2015/701520.(Pubmed)
13. Norjihada Izzah Ismail, Mohammed Rafiq Abdul Kadir, Nasrul Humaimi Mahmood, Om Prakash Singh, Nida Iqbal & Razauden Mohamed Zulkifli, “Apini and Meliponini foraging activities influence the phenolic content of different types of Malaysian honey”, Journal of Apicultural Research, Volume 55, 2016 - Issue 2. Web of Science (IF – 2.084, Q1).
14. Jagannathan Madhanagopal, Om Prakash Singh, Sornambikai Sundaram, Mohammed Rafiq Abdul Kadir, “Enhanced wide range monotonic piezoresistivity, reliability of Ketjenblack/deproteinized natural rubber nanocomposite, and its biomedical application”, Journal of Applied Polymer Science 134:44981 · February 2017. Web of Science (IF – 1.860, Q2).
15. Jagannathan Madhanagopala, Om Prakash Singh, Vikram Mohan, Aatit Paungmali, Kathiresan V. Sathasivam, Abdul HafidzOmar, Mohammed Rafiq Abdul Kadira,”New Device for Intrinsic Hand Muscle Strength Measurement- Alternative to Strain Gauge Hand-Held Dynamometer”, Evaluation & the Health Professions, Volume 20, 2017-Issue 10, Web of Science (IF – 1.306, Q3).
16. Husna Azyan binti Ahmad, Ismail M. El-Badawy, Om Prakash Singh*, Rozana binti Hisham and MB Malarvili,” Fetal Heart Rate Monitoring Device Using Condenser Microphone Sensor – Validation and Comparison to standard Devices”, Technology and Health Care, Preprint (2018): 1-7., Web of Science, (IF-0.724, Q4).
17. Nur Amira Nadia Binti Mohd Shabry, O.P. Singh, Pranshul Sardana, Rozana binti Hisham and M. B. Malarvili, “Home Based Fetal Heart Rate Monitor”, International Journal of Applied Engineering Research, Vol. 12, No. 6, March 2017, pp. 813 ~ 817. ISSN 0973-4562 (Scopus Indexed).
18. Abhay Kumar Gupta, Manish Kumar, O.P. Singh, Malarvili Balakrishnan,“Development of Low Cost and Robust Nursing Calling Device for Hospitalized Patients”,International Journal of Applied Engineering Research, Vol. 11, No. 22, December 2016, pp. 11060 ~ 11064.ISSN 0973 -4562 (Scopus Indexed).
19. Om Prakash Singh, Dr. Hemraj Saini, S. Kalaivani, “A USB Based ECG Portable System and Analysis of Cardiovascular Diseases”, International Journal of Scientific and Engineering Research, Volume 3, Issue 3, March 2012.
20. Om Prakash Singh, S.Kalaivani, “ An Improved Implementation for Brain Tumor and cyst Detection Using Edge Detection, Segmentation with Pixel by Pixel Analysis on CT scan Image” Journal of Engineering, Science and Management Technology, JESMT-2011, Vol.1, No.2, pp. 32-36, July December 2011.

Title: A device for monitoring asthma severity.
Reference number: PI 2018700454 (Filed)
The present disclosure relates to a device for monitoring asthma severity. The available device for monitoring asthma severity is bulky, which makes it difficult to carry around and to transfer from one subject to another. The present invention provides a
device for monitoring asthma severity comprising a carbon dioxide (CO2) acquisitions unit (10), said CO2 acquisitions unit (10) having at least a CO2 nasal cannula unit (12), a water trap unit (14), a pump unit, a motor unit and a CO2 sensor unit (16); a controller module (20) electrically connected to said CO2 acquisition unit (10), said controller module (20) is an Arduino board having a port connectable to a computer and/or a power unit; a display unit (30) electrically connected to said controller module (20), said display unit (30) is a thin film transistor display unit; a real-time control (RTC) module unit (40) electrically connected to said controller module (20) and said display unit (30); characterized in that said device having at least a user operable switch and an LED; and said display unit (30) having a size of 8 cm to 9 cm diagonally.

2. Title: Algorithm for identification of asthma severity level using CO2 waveform
Reference number: LY2018000805 (Approved)
Asthma is known as one of the top causes of death in Malaysia, especially with increased morbidity. Many deaths and morbidity have been associated with poor treatment, under-use of objective measurement of severity level and lack of supervision. A survey carried out by Asthma Council Malaysia indicated that 66% of asthmatic patients have never undergone a lung function test due to high cost, non-portable and lack of availability of diagnostic devices in the clinical set-up in Malaysia. Apart from this, the existing methods (Spirometer and Peak Flow Meter) cannot give accurate result if a patient or children under the age of 6 years old, does not cooperate, suffering from chest pain averting a forceful effort or does not understand the set of instructions. To overcome the limitation of existing diagnostic method, a CO2 waveform that varies in shape based on the CO2 concentration level has been proposed in literature as a noninvasive, real-time, and effort-independent diagnostic and screening tool for monitoring asthmatic condition. However, to date, the studies have been conducted offline in order to extract the features from CO2 waveform in correlation with asthmatic condition. Hence a real time CO2 waveform interpreter screening tool is proposed here for monitoring level of that may lead to reduce the morbidity and mortality rate.

Title: Smartphone Application Based Cardiopulmonary Disorders Monitoring Device iBREATHE
Reference number: IP/CR/2018/1137 (Filed)
Early and effective diagnosis of the COVID-19 infection may greatly help in providing effective support treatment to the COVID-19 patients, and in reducing further spread of the virus which can even put an end to the COVID-19 infection from human society. In that endeavor, we propose the use of a new device which we named as i-breath to screen SARS-CoV-2 infection by analyzing CO2 patterns of a COVID-19 patient .The proposed device has been tested to differentiate respiratory conditions such as asthma, COPD and Covid-19 patients. Our preliminary result proves that it has the ability of classifying different respiratory conditions namely asthma, COPD and Covid-19 based on CO2 features. This report has several limitations. First, information regarding SARS- CoV-2 is limited. Second, information provided here is based on current data, but may be modified as more data becomes available. On the other hand, adding an amalgamation of more covid data from all category (CAT1-5) while developing the device will provide a breakthrough in understanding COVID-19.