Neurology (and neurologists) take pride from being a bastion of clinical medicine - the heart and soul of our practice is listening to our patient and observing their every movement. In some ways neurology has not moved on much (in spirit) from the historic view of 'physicians' portrayed so poignantly by Sir Luke Fields. Movement disorders, and the diagnosis and management of Parkinson's are perfect examples of this human approach, with no equipment other than a tendon hammer necessary to make the diagnosis.
taken from https://www.tate.org.uk/art/artworks/fildes-the-doctor-n01522 with thanks |
It is old hat to say that technology continues at a blistering pace. Miniaturisation has made yesterday's science fiction into the everyday. 'The Fantastic Voyage' described a vessel that was shrunk and inserted into a person's body to save them - well thrombectomy for stroke, stunting for heart attacks, and a video camera so small you can swallow it to get diagnostic pictures throughout the gut are all in routine clinical practice in the NHS today.
The Fantastic Voyage (1966) - picture from https://www.britannica.com/topic/Fantastic-Voyage |
Just a small number of the dizzying array of activity tracking watches available on the high street (picture from Groupon.co.uk) |
The article offers a review on some of the hardware software and statistical approaches to understanding the data. At its heart is the understanding that a neurologist sees their patient for perhaps 3 or 4 15-20 appointments in a year. That clearly leaves 8,759 hours per year where the neurologist has no ability to observe their patient move. Wearable technology brings us a (relatively) non-intrusive window into the 'real lives' of our patients. With the vast amounts of data that this can bring, we need very sophisticated algorithms to understand it, and we need to understand the computer science and mathematical constructs that underlie those algorithms.
Going further than mere observation is prediction - the holy grail in healthcare, and our clearly stated aim in PREDICT-PD. This article concludes by cautioning us about the variation in quality and output of this technology, but offering us the hope that these devices and underlying data analysis will improve clinical decision making, provide more personalised care, and better understand and highlight the differences in the manifestations of what we currently call 'Parkinson's disease', leading to better trials, treatments and one day - cure.
RNR
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