A new collaborative study is working on developing an assistive device based on artificial intelligence that will help with rehabilitation post-stroke.
Recently, a team of researchers showcased BiomacVR, an innovation that aims to assist stroke survivors get back on their feet as quickly as possible. Shortly afterwards, a third component of this technology was developed: BiomacEMG.
According to Rytis Maskeliūnas, study lead, the new system is a part of the Biomac project’s solutions for monitoring the arm. This system will be useful for those patients who need to monitor the movements of the hand or the whole arm during rehabilitation exercises.
The researcher also believes that the integration of motion recognition technology into physical therapy is an innovation that will help patients to focus on the task at hand and perform it more precisely.
Bracelet measures motion
On the new device, Maskeliūnas, says: “Our study evaluated the technical feasibility of measuring and recognising the arm movements of the participants in the experiment, and thus monitoring the rehabilitation or other medical process”.
In order to check the accuracy, researchers chose to measure not only the movements of the whole arm or another large part of the body, but also more precise scenarios, for example, investigating the movements made by the fingers.
This bracelet measures the state of the nerves, muscles and the nerve cells that control them, and is used to measure different types of muscle groups in real time.
Maskeliūnas states that the process is simple – you put the bracelet on your arm and try to make the gestures shown in the picture. The system (or a doctor online) informs you whether you are doing the exercises correctly or incorrectly.
Maskeliūnas, says: “Our team was responsible for the system, and the colleagues from other Lithuanian universities developed the biomechanics model (a model of the muscles and their movements), and carried out the testing.
Beneficial for patient and therapist
Aušra Adomavičienė, a researcher at the Faculty of Medicine at Vilnius University, says: “Our new methodology with electromyography (EMG) elements is particularly important for proper exercise design during a rehabilitation programme. With this new technology, you can see exactly which muscle is working and at what capacity, how it reacts to the load and how quickly it recovers. This information allows the specialist to work with the patient not blindly, but knowing exactly which muscles are working well, which are overworked, or which are not even tired.
“This system is important for the patients with musculoskeletal disorders or diseases that require the restoration of lost movement and mobility function, which is directly caused by reduced or lost muscle function. These are the patients who have suffered a cerebral infarction, various traumas, fractures, soft tissue or nerve damage, systemic diseases such as Multiple Sclerosis or Parkinson’s Disease.”
The researcher points out that this innovative technology can also be used for wellness purposes. For example, for those who, due to irregular, poor working posture, or repetitive movements at work that put a strain on one segment of the body, have muscular imbalances in their bodies, and who often experience chronic pain (back, shoulder or wrist) or fatigue.
According to Adomavičienė, the simple, user-friendly and easy-to-use technology is suitable for people of any age, whether child or adult.
Could this technology be the future?
Adomavičienė, says: “I think that after 20 years, patients and professionals involved in rehabilitation will not even be able to imagine that during functional assessment, testing and programme execution, they were guided by the subjective, hand-held instruments that we now use on a daily basis.”
According to her, computerised and intelligent systems based on artificial intelligence strategies will not only be able to identify in detail the problems experienced by the patient, but after the assessment they will be able to analyse, systematise and provide feedback.
Maskeliūnas agrees with his colleague: “Future research should also look at the development of individualised treatment plans and the adaptation of the algorithm to respond to a wider range of possible actions, taking into account the individual needs of the patient.”
Although the study evaluated the accuracy of the system in measuring hand movement patterns, the long-term impact on functional recovery in stroke patients needs to be further investigated, including the integration of this approach with other therapies such as occupational and physical therapy, according to Maskeliūnas.
