The Applications of Robotics in Healthcare

The field of robotics is becoming increasingly useful in the context of assisting healthcare professionals. Robots can help perform highly technical as well as very mundane tasks, can help reduce the strains and hazards of healthcare work, and can help medical researchers develop new ideas and techniques.  

The word “robot” refers to any physically embodied computational system that can interact with the world around it. Robots take input either through sensors designed to perceive their surroundings or through human controls – or a combination of the two – and manipulate the world around them through “end effectors,” which are specially-designed robotic components which allow them to perform their designated tasks. Think of the robotic hand or clamp at the end of a hydraulic appendage. 

Robots can be expected to be of assistance in the field of healthcare for several reasons. First, some care procedures – especially surgeries – require intense precision. Robots are well-suited to execute very exact movements, even at angles or in contexts that would make it extremely challenging for a human surgeon to achieve the necessary amount of control. Second, robotics can be used to formulate physical simulations of biological structures in order to help medical researchers test novel treatments, prostheses, and therapies. Finally, robotics can help assist with less technical tasks so that clinicians can focus more of their energy on work that makes better use of their training. 

Researchers are developing mobile robots to help automatically deliver medication to patients at the necessary intervals and to respond to basic requests from patients; a robot that could successfully perform these duties would enable clinicians to focus on work that demands their expertise (Shubha & Meenakshi, 2019). Robots can even perform basic social assistance tasks. Some are being developed to engage elderly patients to perform regular exercise and can use wristband sensors to ensure that the workouts remain in healthy ranges of exertion (Salamea et al., 2019). Of course, remote robotic assisted healthcare can also help protect clinicians from exposure to patients with contagious diseases. 

Robots can also assist healthcare professionals with more intense tasks. Researchers who conducted a meta-analysis of 9 papers with 574 total oropharyngeal cancer patients found that transoral robotic surgery “could have [the] advantage for disease-free survival […] compared to [conventional, non-robotic] open surgery” (Park et al., 2020). However, the researchers noted that more long-term comparative studies should be carried out before any strong conclusions are reached.  

Another meta-analysis – this time of 29 studies with 537 total liver resection patients – found that robotic and laparoscopic methods “display similar safety, feasibility, and effectiveness,” while the cost of a robotic surgery tended to be lower than that of a traditional operation (Qiu et al., 2015). On the other hand, the robotic surgeries tended to take longer (Qiu et al., 2015). Researchers conducting a much smaller study of robotic hepatectomy procedures indicated that robotic surgery “might be a good option for [particularly] difficult indications” (Kim et al., 2016).  

The operative effectiveness and cost comparisons of robotic and traditional surgeries are comparable, but considerations of operations’ impacts on surgeons may tip the scales in favor of robotic assisted procedures. Robotic assisted laparoscopy “is significantly less physically demanding” than traditional laparoscopic surgery, “and also feels less strenuous for the surgeons” based on their own subjective reports (Dalsgaard et al., 2018).  

Surgeons each performed 2 hysterectomies, and EMG readings were taken on the surgeons’ upper bodies. These EMG readings were combined with subjective RPE (rate of perceived exertion) data and analyzed to measure the level of exertion. Strain generally decreased, and P values were low across the board, with the highest at .048 and the rest ranging from .037 down to .001 (Dalsgaard et al., 2018). A P value is, roughly speaking, the probability of a particular trend in a data set being purely coincidental. P values range from 1 to 0, with 1 indicating pure coincidence and 0 indicating total certainty in the significance of the observed trend. 

To help develop new therapies and treatments, researchers at University of Bristol have investigated developing a robotic model of the human respiratory system. While the simulation produced was unable to mimic certain high-frequency aspects of human breathing patterns, it was able to reproduce “the frequency, tidal volume, and amplitude of the physiological flow rate profiles of [both] breathing and deep breathing,” as well as “reproduce the volume, flow rate magnitude and duration of a human cough” (Giannaccini et al., 2017). Such simulations of human biological systems may be future testing grounds for new medical techniques. 

As can happen with cutting-edge healthcare techniques and technologies, the sample populations for the testing of robotic assisted procedures are nonrandom. A study of 33,503 patients with rectal cancer found that test subjects are more likely than average candidates to be white, male, privately insured, and graduated from high school. In their analysis, researchers voice concerns that “the inherent bias in access [to robots] may skew study populations, preventing generalizability of robotic surgery research” (Ofshteyn et al., 2019). 

The progress of robotics in healthcare seems promising – procedures may be more effective and may even become more cost effective if technology becomes cheaper, and an increase of robotic assistance seems favorable for patients and for healthcare professionals from researchers to clinicians. However, if robots are ever to enter the mainstream of healthcare, research must first indicate that robotic care remains successful even when tracked on longer timescales, and that its implementation remains effective even when extended to populations on which it has not yet been sufficiently tested. 

References 

Dalsgaard, T., Jensen, M. D., Hartwell, D., Mosgaard, B. J., Jørgensen, A., & Jensen, B. R. (2018). Robotic Surgery Is Less Physically Demanding Than Laparoscopic Surgery. Annals of Surgery, 271(1), 1. https://doi.org/10.1097/sla.0000000000002845 

Giannaccini, M. E., Yue, K., Graveston, J., Birchall, M., Conn, A., & Rossiter, J. (2017). Respiratory simulator for robotic respiratory tract treatments. 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO). https://doi.org/10.1109/robio.2017.8324764 

Kim, J. K., Park, J. S., Han, D. H., Choi, G. H., Kim, K. S., Choi, J. S., & Yoon, D. S. (2016). Robotic versus laparoscopic left lateral sectionectomy of liver. Surgical Endoscopy, 30(11), 4756–4764. https://doi.org/10.1007/s00464-016-4803-3 

Ofshteyn, A., Bingmer, K., Towe, C. W., Steinhagen, E., & Stein, S. L. (2019). Robotic proctectomy for rectal cancer in the US: a skewed population. Surgical Endoscopy, 34(6), 2651–2656. https://doi.org/10.1007/s00464-019-07041-0 

Park, D. A., Lee, M. J., Kim, S.-H., & Lee, S. H. (2020). Comparative safety and effectiveness of transoral robotic surgery versus open surgery for oropharyngeal cancer: A systematic review and meta-analysis. European Journal of Surgical Oncology, 46(4), 644–649. https://doi.org/10.1016/j.ejso.2019.09.185 

Qiu, J., Chen, S., & Chengyou, D. (2015). A systematic review of robotic-assisted liver resection and meta-analysis of robotic versus laparoscopic hepatectomy for hepatic neoplasms. Surgical Endoscopy, 30(3), 862–875. https://doi.org/10.1007/s00464-015-4306-7 

Salamea, H. M. T., Cedillo, P. A. S., Alvarado-Cando, O., & Auquilla, A. R. (2019). Health Care in the Older Adult by Means of a Bioloid Robot as a Social Assistive to Motivate Physical Exercise. 2019 7th International Engineering, Sciences and Technology Conference (IESTEC). https://doi.org/10.1109/iestec46403.2019.00097 

Shubha, P., & Meenakshi, M. (2019). Design and Implementation of Healthcare Assistive Robot. 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS). https://doi.org/10.1109/icaccs.2019.8728363