Girish Tilekar

Bio: Girish Tilekar is an academic researcher from Cranfield University. The author has contributed to research in topics: Grippers. The author has an hindex of 1, co-authored 2 publications receiving 4 citations.

Severity Monitoring Device for COVID-19 Positive Patients

Abstract: In this paper we have designed an intelligent wearable device and developed the corresponding algorithm, for COVID-19 positive patients that is capable of predicting and notifying the increase in severity of the virus. The device uses ESP 32: Node MCU, MAX 30102: Pulse Oximeter and Heart rate sensor, LM35: Temperature sensor and a vibration sensor. This device will monitor the patient's body condition such as heart pulse rate, oxygen saturation level, body temperature, hand movements due to restlessness and process this information simultaneously. Consequently, when the virus is predicted to advance to its next stage, an alert will be sent to the person taking care of the patient. Hence, this device will inform when the patient is advancing from mild to the moderate or serve condition of COVID-19. The paper gives a deep understanding on the use of this device.

Design of Enlarging Vacuum Gripper Using Slider Crank Mechanism

Abstract: Varieties of robotic grippers are developed with high flexibility and multi-functional approaches. In this paper, the study and design of an innovative approach of a gripper for handling variable size, shape and weight is proposed. This paper proposes a gripper that is capable of changing the distance between its two opposite grippers. For this purpose, we use slider crank mechanism which is actuated by servo motors. The paper gives a deep understanding and the use of this type of gripper.

The Rise of Wearable Devices during the COVID-19 Pandemic: A Systematic Review.

Abstract: The COVID-19 pandemic has wreaked havoc globally and still persists even after a year of its initial outbreak. Several reasons can be considered: people are in close contact with each other, i.e., at a short range (1 m), and the healthcare system is not sufficiently developed or does not have enough facilities to manage and fight the pandemic, even in developed countries such as the USA and the U.K. and countries in Europe. There is a great need in healthcare for remote monitoring of COVID-19 symptoms. In the past year, a number of IoT-based devices and wearables have been introduced by researchers, providing good results in terms of high accuracy in diagnosing patients in the prodromal phase and in monitoring the symptoms of patients, i.e., respiratory rate, heart rate, temperature, etc. In this systematic review, we analyzed these wearables and their need in the healthcare system. The research was conducted using three databases: IEEE Xplore®, Web of Science®, and PubMed Central®, between December 2019 and June 2021. This article was based on the PRISMA guidelines. Initially, 1100 articles were identified while searching the scientific literature regarding this topic. After screening, ultimately, 70 articles were fully evaluated and included in this review. These articles were divided into two categories. The first one belongs to the on-body sensors (wearables), their types and positions, and the use of AI technology with ehealth wearables in different scenarios from screening to contact tracing. In the second category, we discuss the problems and solutions with respect to utilizing these wearables globally. This systematic review provides an extensive overview of wearable systems for the remote management and automated assessment of COVID-19, taking into account the reliability and acceptability of the implemented technologies.

IoT based Smart Healthcare System to Detect and Alert Covid Symptom

Abstract: There is a rapid increase in the spread of the Covid Virus. This has resulted in serious health issues among people. There is a dire need for a proper system to detect COVID symptoms and Alert Officials. The proposed solution is an IoT based multiple Health Monitoring System to detect symptoms of COVID and alert officials. It consists of a contactless temperature sensor, Oximeter, Automatic Hand Sanitizer, Camera module, Room Occupancy limiter and a Social Distancing module. It is a contactless method for patient evaluation. The Internet of Things enables devices to connect to the internet and communicate with each other. Data from these IoT-connected devices will help to identify the scenario and take necessary action. Contactless Temperature Sensor, Oximeter, and Heartbeat rate sensors are used to measure temperature, Oxygen level, and Heart rate respectively. NodeMCU reads sensor values, ESP32 camera module capture picture, and stores for future reference. The sensors measure the data. Normal temperature reading is from 97°F to 99°F and normal SpO2 reading is at least 95% [1]. If the measured value crosses the normal value, those details are immediately sent to health workers with a picture of the individual. The proposed solution also consists of a module to maintain Social Distancing and also an automatic Hand Sanitizing module. As the entire setup is automated, it reduces time and labour and also ensures satisfactory results.

A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine

Abstract: Since 2019, the COVID-19 pandemic has had an extremely high impact on all facets of the society and will potentially have an everlasting impact for years to come. In response to this, over the past years, there have been a significant number of research efforts on exploring approaches to combat COVID-19. In this paper, we present a survey of the current research efforts on using mobile Internet of Thing (IoT) devices, Artificial Intelligence (AI), and telemedicine for COVID-19 detection and prediction. We first present the background and then present current research in this field. Specifically, we present the research on COVID-19 monitoring and detection, contact tracing, machine learning based approaches, telemedicine, and security. We finally discuss the challenges and the future work that lay ahead in this field before concluding this paper.

HealthyLungs: Mobile Applications for Round-the-Clock Remote Monitoring of Lung Function in Patients with COVID-19

Abstract: The paper proposes smartphone applications, that allow doctors to continuously observe the main organ of patients, affected by the coronavirus, – the lungs. The applications are based on wireless devices and designed in a way to monitor the state of patients’ lungs round-the-clock and regardless of their location. Therefore, created applications allow the doctor continuously and remotely (e.g. from their office) see the level of oxygen in the patient’s blood. These data from the pulse oximeter with a wireless connection will be send via the patient’s smartphone to the server, where the doctor will receive information about the patient’s condition and can decide on further treatment. With these applications, doctors will be able to monitor the condition of their patients, who are in hospital wards as well as at home, on observation or outpatient treatment. What is important, this way it will be possible to track the condition of the sick not only with Covid-19 but also with other diseases, for example, asthma, vascular diseases or cancer.

IoT Based Remote COVID-19 Patients Monitoring System for Local Hospitals in Sri Lanka

Abstract: The current Coronavirus (Covid-19) pandemic caused by the upcoming SARS-CoV-2 category has terrified human health worldwide. It has resulted in millions of demises, threatening the elderly and people with chronic diseases. Most healthcare institutions are facing congestion and the lack of resources during this period, and it has also become an unbearable issue to have no accommodation capacity in hospitals, where patients can no longer be accommodated. This paper proposes a cost-effective intelligent patient monitoring system for the Covid-19 patients’ wards in Sri Lankan Hospitals using IoT and Cloud Computing technologies which helps identify high-priority patients based on their health conditions. Continuous monitoring of the ward's environmental factors helps to ensure that it is a safe environment for Covid-19 patients. Moreover, it ensures safeguarding medical staff by reducing interactions with patients and enforcing safety measures in the hospital environment by face mask detection. The research was performed by implementing a proof of concept with systematic testing and qualitative analysis.