German researchers are developing motion analysis software to spot early signs of arthritis, a joint disease that forces millions around the world to undergo surgery every year.
The project at the Karlsruhe Institute of Technology (KIT) wants to determine changes in gait of patients early after the onset of the condition to help deliver the diagnosis and advise treatment before the patient even starts having problems.
“Based on a computer-supported gait analysis, we want to develop an early warning system for routine prevention,” said Professor Stefan Sell, of the Institute of Sports and Sports Science at the KIT. “In this way, we can also develop and test gentler motion sequences for patients. At an early stage, even sports might be helpful, provided that it is executed correctly.”
The researchers assume that slight changes in motion occur as the wear of the joints sets in. Subconsciously, affected patients start compensating for the damage by, for example, shifting body weight to the other side to relieve tension.
The team is now compiling a catalogue of human motion patterns, mathematically analysing deviations and the probability of their occurrence.
To find the difference between the healthy and unhealthy gait, the researchers are working with arthritis sufferers as well as fit individuals. Using the same methods as employed in virtual reality applications, the researchers are collecting data from the tested subjects by attaching 39 markers to their bodies and letting them walk under infrared light.
As the tested subject moves under the infrared light, the light is reflected by the markers and recorded by cameras. On the computer, the joint markers appear as image points, allowing the scientists to model the body and its motion.
In addition, the values of two force measurement plates are recorded. If a tested person walks across these plates, they measure when and where his or her foot touches the plate and what force it applies to the surface. Light barriers in front of and behind the force measurement plates record the average speed.
“Using these values, our calculation models can identify various motion patterns: They can determine whether somebody walks or runs, whether he moves on plane ground or climbs a slope,” said Andreas Fischer of the KIT.
The researchers believe they will be able to develop such precise algorithms to distinguish individual persons by their motion patterns.
For now, differentiating between the healthy test subjects and arthritis sufferers would be sufficient.
“With them we observe common features of motion sequences, which are highly improbable for healthy people,” Fischer said, explaining that in many cases knee movements of arthritis sufferers are limited and weight tends to be shifted more slowly to the aching leg in order to reduce the shock when the foot is put down.
The project is only in its early stages and would take at least two years to progress the technology sufficiently for commercialisation.
Arthritis is an excessive wear of joints beyond what is normally caused by aging. A widespread issue in the modern population, arthritis forces millions of patients around the world every year to undergo joint replacement surgeries, which are painful and require complex rehabilitation. Early diagnoses could help prevent or at least slow down the condition from progressing by advising mitigation strategies and treatment.