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Parkinson’s Disease and the Internet of Things

Healthcare and the internet of things.

Introduction

The healthcare industry has been evolving to meet the needs of the rapidly changing digital environment. The industry has utilised the use of emerging technologies to enhance productivity and ultimately improve patient experience and quality of life.

In this blog, I will be focusing on the Internet of things or IoT. So, what is the internet of things? The basic concept behind IoT is that everyday objects interconnect with each other through a networked system. These objects often are equipped with ubiquitous intelligence (Xia et al., 2012). The healthcare industry used IoT extensively, creating its branch called the medical internet of things (mIoT). This technology implements wireless sensors in medical equipment, combining with the internet integrating, hospital, patient, and medical records, promoting a new medical model (Hu, Shen, and Xie, 2013).    

The treatment of Parkinson's disease incorporating the medical internet of things will be at the heart of this blog. PD is a condition in which parts of the brain become progressively damaged over many years. One of the most detrimental and noticeable symptoms of this disease is the involuntary shaking of particular parts of the body, also known as a tremor (NHS Choices, 2019).  

Theory behind the Technology

The underlying treatments using IoT to treat PD are through wearable technology, home monitoring, and digital versions of standardised clinical tests. Wearable sensors are being specifically designed to capture disease traits that are prevalent in PD such as, tremor episodes, gait patterns, and activity levels. These devices can be hooked up to the internet through data aggregators, where the information is sent to medical and research databases and is then sent back to the patient in the form of visual and other sensorial cues. (Pasluosta et al., 2012). The relationship between IoT and the healthcare system can be shown in figure 1.

The traditional treatment of PD patients must attend clinical appointments to assess their postural instability and tremor level. The costs of this involve patient transportation, consultation, and hospital resources. The opportunity to perform at-home procedures using sensors and the IoT would reduce these costs significantly. Also, standard assessments of PD from a clinician can often be subjective. This makes the patients’ health dependant on the clinician’s experience and expertise. If a form of sensory technology can be implemented, more objective results may be found (Romero, Chatterjee, and Armentano, 2016). An IoT remote treatment model can be shown in figure 2. 

Albani et al. (2019) researched the effectiveness of a multi-sensor approach in treating PD. These strategies aimed to reduce the frequency of follow-up appointments for PD patients. And improve the accuracy of results. They concluded that the proposed solution of sensor wearable technology significantly improved the assessment of PD. Providing a decentralised, more accurate, and cost-effective method of treating PD. 

Application of technology

After consulting the academic theory surrounding the IoT and its role in the medical internet of things, it is important to examine which institutions have been successful in implementing this technology.  Intel has partnered with the Michael Fox Foundation for Parkinson’s research to find tech-enabled solutions to PD. The project aimed to produce a mobile application and IoT platform to support large case studies of objective sampled sensory data for people with PD (Cohen, Bataille, and Martig, 2016).  Intel used on-the-shelf wrist-worn smartwatches and built an application around them which is downloaded on a smartphone and calibrated with the watch. These devices also share data with the Fox Foundation servers. The smartwatches served two functions: to track patient activity, tremors and pass data to the ‘enterprise data hub’ for big data analysis. The Fox mobile app is a big part of this product. The layout of the application is shown in figure 3. The mobile app allows users to input information about their medication and medication schedule. The data is stored in the cloud for analysis and storage (Intel corporation 2015).

Challenges

 With any promising technological outbreak and achievement, challenges always present themselves. The medical internet of things and the treatment of PD is no different. Dimitrov (2016) highlighted five key capabilities a leading IoT system must have:

Simple connectivity, making it easier to     connect devices and scale through cloud base services for data analysis.

Easy device management, improve asset     availability, and reduce maintenance costs.

Information Ingestion, intelligently transform     and store IoT data.

Informative analytics, make informed decisions     based on large volumes of IoT data to optimise procedures. And to apply     real time analytics to monitor current conditions and respond accordingly.

Reduced risk, react to notifications, and     isolate any incidents generated from the company environment from any     device/console.    

 Reflections

Reflecting on this blog discussion it is clear that the IoT/ mIoT can have a positive impact on the battle against PD. In particular, the use of wearable technology. And how this can collaborate with the IoT to produce objective results, making cost savings for health organisations all over the world. With an aging population, PD is likely to become more prominent. An effective IoT system allows for a decentralised approach making significant improvements in Hospital efficiency and patient conditions. The Intel and Fox app is exciting, and it's fascinating to see where this sort of technology can go and the differences it can make to people's lives in the health industry.

References

Albani, G., Ferraris, C., Nerino, R., Chimienti, A., Pettiti, G., Parisi, F., Ferrari, G., Cau, N., Cimolin, V., Azzaro, C., Priano, L. and Mauro, A. (2019). An Integrated Multi-Sensor Approach for the Remote Monitoring of Parkinson’s Disease. Sensors, 19(21), p.4764.

Chatterjee, P. and Armentano, R.L., 2015, December. Internet of things for a smart and ubiquitous eHealth system. In 2015 international conference on computational intelligence and communication networks (CICN) (pp. 903-907). IEEE.

Cohen, S., Bataille, L.R. and Martig, A.K. (2016). Enabling breakthroughs in Parkinson’s disease with wearable technologies and big data analytics. mHealth, 2, pp.20–20.

Dimitrov, D.V. (2016). Medical Internet of Things and Big Data in Healthcare. Healthcare Informatics Research, 22(3), p.156.

Hu, F., Xie, D. and Shen, S., 2013, August. On the application of the internet of things in the field of medical and health care. In 2013 IEEE international conference on green computing and communications and IEEE Internet of Things and IEEE cyber, physical and social computing (pp. 2053-2058). IEEE.

Intel Corporation, Michael J. Fox Foundation. Using wearable technology to advanced Parkinson’s Research 2015. Available online: www.intel.com/content/dam/www/public/us/en/documents/white-papers/using-wearable-technology-mjff.pdf

NHS Choices (2019). Overview - Parkinson’s disease. [online] NHS. Available at: https://www.nhs.uk/conditions/parkinsons-disease/.

Pasluosta, C.F., Gassner, H., Winkler, J., Klucken, J. and Eskofier, B.M. (2015). An Emerging Era in the Management of Parkinson’s Disease: Wearable Technologies and the Internet of Things. IEEE Journal of Biomedical and Health Informatics, [online] 19(6), pp.1873–1881. Available at: https://ieeexplore.ieee.org/abstract/document/7169494/ [Accessed 23 Feb. 2020].

Romero, L.E., Chatterjee, P. and Armentano, R.L. (2016). An IoT approach for integration of computational intelligence and wearable sensors for Parkinson’s disease diagnosis and monitoring. Health and Technology, 6(3), pp.167–172.

Xia, F., Yang, L.T., Wang, L. and Vinel, A. (2012). Internet of Things. International Journal of Communication Systems, 25(9), pp.1101–1102.