Robotic Technologies in Biomedical and Healthcare Engineering

Deepak Gupta, Moolchand Sharma, Vikas Chaudhary, Ashish Khanna, Deepak Gupta, Moolchand Sharma, Vikas Chaudhary, Ashish Khanna

• Publisher: CRC Press
• Year: 2021
• ISBN:
  9781000405149
• Edition: 1
• Topic: Medicine
• Subtopic: Biotechnology in Medicine

New prospects for biomedical and healthcare engineering are being created by the rapid development of Robotic and Artificial Intelligence techniques. Innovative technologies such as Artificial Intelligence, Deep Learning, Robotics, and IoT are currently under huge influence in today's modern world. For instance, a micro-nano robot allows us to study the fundamental problems at a cellular scale owing to its precise positioning and manipulation ability; the medical robot paves a new way for the low-invasive and high-efficient clinical operation, and rehabilitation robotics is able to improve the rehabilitative efficacy of patients. This book aims at exhibiting the latest research achievements, findings, and ideas in the field of robotics in biomedical and healthcare engineering, primarily focusing on the walking assistive robot, telerobotic surgery, upper/lower limb rehabilitation, and radiosurgery. As a result, a wide range of robots are being developed to serve a variety of roles within the medical environment. Robots specializing in human treatment include surgical robots and rehabilitation robots. The field of assistive and therapeutic robotic devices is also expanding rapidly. These include robots that help patients rehabilitate from severe conditions like strokes, empathic robots that assist in the care of older or physically/mentally challenged individuals, and industrial robots that take on a variety of routine tasks, such as sterilizing rooms and delivering medical supplies and equipment, including medications. The objectives of the book are in terms of advancing the state-of-the-art of robotic techniques and addressing the challenging problems in biomedical and healthcare engineering. This book

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• Lays a good foundation for the core concepts and principles of robotics in biomedical and healthcare engineering, walking the reader through the fundamental ideas with expert ease.

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• Progresses on the topics in a step-by-step manner and reinforces theory with a full-fledged pedagogy designed to enhance students' understanding and offer them a practical insight into the applications of it.

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• Features chapters that introduce and cover novel ideas in healthcare engineering like Applications of Robots in Surgery, Microrobots and Nanorobots in Healthcare Practices, Intelligent Walker for Posture Monitoring, AI-Powered Robots in Biomedical and Hybrid Intelligent Systems for Medical Diagnosis, and so on.

Deepak Gupta is an Assistant Professor at the Maharaja Agrasen Institute of Technology, GGSIPU, Delhi, India.

Moolchand Sharma is an Assistant Professor at the Maharaja Agrasen Institute of Technology, GGSIPU, Delhi, India.

Vikas Chaudhary is a Professor at the JIMS Engineering Management Technical Campus, GGSIPU, Greater Noida, India.

Ashish Khanna currently works at the Maharaja Agrasen Institute of Technology, GGSIPU, Delhi, India.

1 IoT-Integrated Robotics in the Health Sector

Rehab A. Rayan

Alexandria University

Christos Tsagkaris

University of Crete

Imran Zafar

Virtual University of Pakistan

Contents

Introduction

History

Health Robotics

Applications of Robotics in the Health Sector

The Health IoT

IoT-Based Robotics Framework

Discussion

Opportunities and Challenges

Future Insights

Conclusions

References

Introduction

Nowadays, the elderly population is growing worldwide with an increase in comorbidities due to their unhealthy modern habits like smoking, increased alcohol consumption, unhealthy diet, obesity, and the lack of physical activity. The World Health Organization (WHO) predicts that the health Internet of things (IoT) industry will explode, costing billions of dollars. Gradually, the IoT start-ups are introducing modern healthcare applications for integrating networked sensors to improve diagnosis, monitoring, and treatment of patients. Such applications are medical wearables for active monitoring of patient data or hospital networks and procedures, optimizing healthcare delivery and monitoring patient compliance (WHO 2013).

IoT is a promising option in the health sector, connecting applications, devices, and people to improve management of diseases with better outcomes and fewer errors, thus ensuring high efficiency and safe healthcare at lower costs (Patel et al. 2017). Integrating swiftly advancing technologies such as robotics, machine learning (ML), and the IoT could shift the way of living. Robotics involves machines programmed for labor-intensive jobs, while ML implies that computers and other devices operate with no prior programming. Integrating robotics and ML gives rise to robots that function independently. ML techniques range from supervised and semi-supervised learning to unsupervised learning, including pattern recognition statistically, parametric or non-parametric algorithms, neural networks, and other systems. ML coupled with the IoT could link many robots facilitating networking among individuals and things, sending data without intervening, and hence collecting and monitoring data within the network, for example, monitoring the environment, managing infrastructures, energy, and productions, and digitizing buildings, houses, transportation, and the health sector.

This chapter discusses the applications of adopting robotics and the IoT in the health sector. It explores the integration of robotics with the IoT for health applications, opportunities, and limitations, along with future insights.

History

The term “Robot”, derived from the term “Robota”, implying obligatory worker, was initially introduced in a play in 1921. The Robotics Institute of America defines a robot as a likewise human machine that is programmed to operate insensitively to the mechanical tasks of a human. In the 1940s, robots were regulated by three rules: causing no harm to humans, complying with human orders unless those breaching the first rule, and securing their own presence unless such security conflicts with the first or second rule. Robots were primarily designed to function similarly to man, and later, with added characteristics, they turned into smart machines.

Health Robotics

In the health sector, robots carry out coordinated tasks such as patient monitoring, clinical interventions, artificial prosthetics, rehabilitation, and e-health, applying electronics and mechanics such as measuring space, motion, or force, sensor technology, and others (Butter et al. 2008). Robotics could be valuable from the economic, social, and healthcare aspects where they could particularly benefit patient groups with special needs like amputees, stroke survivors, or those with mental insufficiencies. In the health sector, robotics could be applied in intelligent medical capsules, surgeries, prosthetics, analyzing and managing motor coordination, robot-aided social and cognitive treatment, and patient monitoring systems (Butter et al. 2008).

Lately, the medical robots’ market is growing, and they are being used broadly worldwide in healthcare since they could evidently function timely at minimal risk, for example, in cardiac and prostatic operations, rehabilitation, and smart prosthetics. Social robotics could monitor and motivate patients (Martinez 2020). The exponential rise in innovative applications of robotics in the health sector is brought by the increasing need for information technology, which would derive future growth in the market. Globally, more application of the least invasive surgical robots is coupled with population growth, maintaining robustness in disorders like orthopedics, neurological disorders, and others. Adopting robotics is witnessed to be promising in countries such as China, India, and Brazil (Martinez 2020).

In today’s surgical operations, computer-integrated systems perform more precisely than surgeons, especially in unfavorable settings where they provide technical solutions and smoothly monitor operations-needed data online added to operating on sensitive anatomical structures in dangerous proximity settings. Robotics, a multidisciplinary domain, linking the data in real world with the physical one, integrating engineering, computational science, biomechanics, sports science, biomedicine, neurology, cognitive science, and others, and hence coordinating sensors, motors, and humans, is challenging in various settings (Taylor 2006).

When using robotics in the health sector, the structure, movement, and intelligence, among other factors, should be considered. The structure describes the human engaging levels in supervising the functioning robots in typical procedures, especially when encountering system errors. The movement comprises programmed pathways for motion within the environment. Intelligence describes the inherent expert skill or knowledge facilitating carrying out jobs with minimal skill or knowledge than expected for a human doing the same job (Bakhru 2017).

Applications of Robotics in the Health Sector

In prevention, no treatment is required; however, for any detected abnormality, the diagnosis could be done by a robot (Butter et al. 2008). For instance, Toyota has designed the Balance Training Assist where a two-wheel robot displays games on the monitor using the data fed into the machine while the patient moves his/her weight (Toyota 2019). Using robots in surgeries would enable accuracy, reliability, and consistency acting on the human body especially in tiny spaces compared to physicians’ performance, for instance, in microsurgery, minimally invasive surgery, nanobots, remote surgery via the IoT systems, robotics-assisted surgery, and other medical interventions. Nanobots, also called steerable surgeons, are applied in ocular disorders, for which they are manufactured with flat nickel elements and operated on magnetic fields using extrinsic electromagnetic coils (Tomlinson 2018).

Hospital robots for professional care are used for the aging population, for monitoring, assisting healthcare providers, providing physical activities, and other paramedic jobs (The Journal of mHealth 2018). For instance, Cody, a humanoid portable operator, applies direct physical interface (DPI) to help a healthcare provider in directly managing robot mobility, which in turn directly contacts the human body and responds to the patient’s motion (Grifantini 2010).

Rehabilitation is provided in a healthcare facility or at home and includes sustaining muscle or motor coordination therapies. The behavior of patients is a key player in mental disorders. In the cerebral and nervous muscular system disorders, the brain functions inadequately and might cause disabilities in the lower extremities. Hybrid assistive limb, a cyborg-kind robot, could support and improve the wearer physically via supporting the lower extremities in movement based on the patient’s needs (Ackerman 2018; Lazarte 2014). Robots can assist in everyday life activities such as performing those activities, supporting the movement for the disabled, and substituting organs via smart prosthetics. For example, Friend, the electrical wheelchair, is composed of a robotic arm, a computer, sensors, and joysticks to work on the system enabling the individual to read a book while turning pages (Souppouris 2012).

The Health IoT

The IoT can be vaguely defined as the Internet-based interconnection of computing devices embedded in everyday objects, enabling them to send and receive data. The IoT applications can be summarized with the following four principles: data collection, data conversion, data storage, and data processing. Interconnected devices including sensors, monitors, detectors, equators, and cameras collect data. Their input is converted from the analog form to the digital form enabling further processing. As data accumulate, storage is facilitated by means of cloud-based systems. At the end of the day, further data processing through advanced analytic modalities provides healthcare professionals with information necessary for decision-making (Psiha and Vlamos 2017; Latif et al. 2017; O’Brolcháin, de Colle, and Gordijn 2019). Although the human healthcare workforce can follow these principles as well, the IoT ensures the continuous flow of data facilitating instant decisions.

In the context of healthcare, IoT applications are expected to focus on research, clinical practice, and patient management, which are greatly discussed. Using the IoT in the healthcare system enables monitoring chronic diseases, care for elderly patients, and managing healthcare systems, among others. The IoT in the health sector could be service- or application-centered as shown in Figure 1.1. To the extent that insurance and industry intersect with healthcare, IoT applications in these fields may also impact healthcare (Mittelstadt 2017; Psiha and Vlamos 2017; Bandyopadhyay and Sen 2011; Gopal et al. 2019). When it comes to patients, the IoT infrastructure consists mostly of wearable devices. Wearables may include monitors for oxygen saturation, blood pressure, pulse/heart rate, and glucose level depending on the history of the patient and the parameters that should be monitored (Özdemir and Hekim 2018; Gopal et al. 2019; Gope and Hwang 2016). When it comes to physicians, the IoT offers real-time connection to their patients, to their colleagues, and to their clinic or laboratory. A cardiologist can be notified about an arrhythmia affecting one of his patients and a diabetologist can be informed about hypoglycemia threatening one of his patients. In both cases, the patients can have immediate medical guidance and support. At the same time, physicians can assess patients’ adherence. It is not only a matter of outcome – e.g. blood pressure increases in case patients neglect their treatment – it can also be a matter of device monitoring. The delivery of this information to remote healthcare providers, such as a physician supervising a nursery home or a specialist consulting patient residing in remote communities, is also of great importance (Chai et al. 2019; Stefano and Kream 2018).

FIGURE 1.1 Health IoT.

IoT-Based Robotics Framework

The Internet would connect the robot’s real and virtual world including the evolving robotic operating system (ROS), connectivity with the Bluetooth, and an application programming interface (API) as shown in Figure 1.2, where the robot would be a component of the IoT and could smoothly communicate with the cloud. Such robots are promising to have intelligent mobility and setting-oriented computing to the Internet relevant to the close physical ecosystem. The cloud would enable the robot to communicate either asynchronously or synchronously with any device, service, or business process on the cloud.

FIGURE 1.2 The IoT-...