Right Step's mission is to support those who suffer from degenerative bone disorders. This is a tall task as there is still substantial knowledge gaps concerning the underlying mechanisms.
In the quest for lunar habitation and the exploration of space astronauts suffer from degenerative bone disorders along with many other physiological complications at an accelerated rate compared to Earth. Physiological research is on going of which Right Step is active participant where we carry out our own experiments and provide our tools and platforms to support others that share our goals.
Initially we focussed on skeletal loading which gave birth to Osteosense for healthcare and presented unique opportunities to study bone health, countermeasures and further the knowledge in degenerative bone disorders more broadly. Recently this has led to a collaboration with Taltech (Tallinn University of Technology) supported by the Estonian Research Councils Sekmo programme which focus' on the development of sensor technology for use in healthcare settings. With osteosense and its underlying algorithms coupled with
Environmental Sensing and Intelligence Group's expertise a tool to classify osteoarthritis (OA) is now reaching prototype stages.
A common manifestation of OA is knee OA which affects millions of people often resulting in a replacement. Imaging techniques are typically used as the primary diagnostic that have a variety of limitations from reduced resolution to cost and time of acquisition. Ultrasound offers a promising alternative yet it is currently limited by sounds properties resulting in parts of the joint being hidden.
Back in 1987 Mccoy et al coined the term "vibration arthrography" which involves the "detection and recording vibration emission from human joints". The outcome was a promising non invasive technique for the diagnosis of knee disorders. The initial paper can be found here: Vibration arthrography for knee diseases - Preliminary report. The history leading to this technique dates back to 1885 with the use of the stethoscope.
VAG as it is now referred to has progressed substantially as microphone and accelerometer technology has developed. The developments in sensors and signal processing makes VAG a real proposition for early detection of OA which could have substantial impact on healthcare systems' ability to improve the management and treatment of patients, reduce cost and overall burden on already stretched institutions.
Accelerometry has a few advantages in that today's sensors are very small allowing multiple devices to be used and easily placed around the knee. The sensitivity and frequency response of these devices allows the "listening" to signals in high frequency bands, typical of VAG signals. There has been a variety of studies that have explored positioning of and number of sensors with the most optimal location being reported as the medial compartment below the midline of the patella. There is however, an argument to utilise multiple sensors around the knee joint since different VAG signals are emitted from different locations.
The basic, and most simple setup involves a single accelerometer positioned on the medial compartment with the patient instructed to flex and extend the knee from a seated position. The speed of the activity is seemingly important as some signals are only present with a slow moving knee. Studies have used a metronome to assist with this. Outcomes have been pretty reliable in repeated measurements on the same day with a drop in repeatability on successive days. Therefore some control of the previous knee activity is required to ensure accuracy.
The VAG signals must be pre processed post acquisition (or in near real time) in order to remove artifacts such as baseline wander, random noise, and muscle activity. Typically this is done via filtering techniques. Following pre processing VAG signals are further processed to extract features for use in classification. Features are extracted in the time domain, frequency domain or the time-frequency domain and have yielded accuracy levels as high as 91.4% which incidentally is as good as if not an improvement on current diagnostic methods. Interestingly Right Step's skeletal loading algorithms are not to far removed from VAG analysis methods making this avenue ideal for Right Step. there is potential to apply these techniques to other pathologies and other joints of the human body.
Right Step and Taltech will deliver a simple and effective tool to diagnose OA grades as part of Right Step's Osteosense suite of tools. Consisting of high performance accelerometers, low energy bluetooth communication and dedicated software, the solution will enable a simple, accurate and cost efficient means to screen patients reducing the need for expensive imaging, reducing burden and providing patients with the correct course of action. In the quest of lunar habitation simple and effective diagnostic methods are a must to remain healthy in remote and extreme environments.
If this sounds interesting to you then please do get in touch, whether to learn more, check in regarding our progress or to try out the tools we are always open.
Much of the information provided here can be found in the paper,
"Review of the Vibration Arthrography Technique Applied to Knee Diagnostics"
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