Congratulations to Peyman and PACER team for approved Research Council of Norway application “Patient-Centric Engineering in Rehabilitation (PACER)” for 10 MNOK.
The project is a collaboration between dep. of MEK (TKD, HiOA), and motion analysis lab
(HF+TKD), Simula Center, Dep. of Occupational Therapy, Prosthetics and Orthotics (HF), dep. of IT
(TKD), Dep. of Product Design (TKD) and the Research Centre CAIR, at the University of Agder
(UiA). Project collaboration partners as University of Southampton, University of Washington, Dublin City University, and Maynooth University
are chosen because of their excellent qualifications to reinforce our training program in an international
With this grant and funding from TKD, the team will have funding for 4 PhD students that will work in a highly multi-disciplinary environment and focus on making a device that facilitates an optimized and personalized rehabilitation environment for amputates with lower limb.
Background and knowledge needs:
In the western world, about 50% of major amputations is caused by diabetes, and the majority of these have had a long and complex medical history. They have often been too inactive, had pain and impaired general condition. It is critical that these people are motivated to take back control of their lives, and assisted to increase their quality of life. We believe that a device that could follow the patient will facilitate for a personalized and optimized rehabilitation. To the best of our knowledge we have not found any attempts to apply such scoring rules on machine learning, artificial neural network or deep learning models in a personalized and optimized device for rehabilitation of amputated patients.
As a pacer allows the runner to focus exclusively on their running, without having to expend any mental energy on their pace, we believe that a device that could follow the patient gives a possibility for a personalized and optimized rehabilitation. What makes the patient-centric rehabilitation is that the information and interaction emanates from the patient. As the wireless technologies with sensors, recently termed as the Internet of Things (IoT), are built around the premise that personalized data and interactions are prompted by the patient and managed by both patient and provider, IoT is making pulling data from different heterogeneous devices increasingly ubiquitous. IoT also permits closing the analysis loop by offering unified platforms for data aggregation and analysis including Big data platforms such as Map-Reduce clusters.
Furthermore in a patient-centric rehabilitation, the patient as a source creates the information. As there is a large amount of data created from the patient, the bid data can be filtered with patient specific mined data based on machine learning principles. As early as in 1959, Arthur Samuel resorted to the notation Machine Learning to measure the ability of a computer to handle decision cases that it is not explicitly programmed to perform. IBM Watson Health is expected to revolutionize the field of healthcare and especially the way diagnosis is performed. The faculty of TKD, HiOA has just recently signed a collaboration agreement with IBM Watson “Blue mix” technology making this system available to our researchers.
On the other side of the coin, the people who learn this concept through this project, will learn how to interact with other professionals at their own pace, which may cultivate a long-lasting collaboration, enabling the future doctorates to be better prepared for the challenges of the future health care system. The benefits of interprofessional collaborations are improved patient outcomes, enhanced provider satisfaction, and more effective utilization of resources, while the challenge is increased competition for the time of health care professionals.
Need for an autonomous device
Lower Limb amputation (LLA) is not only related to trauma such as traffic accidents, but also to diseases such as diabetes mellitus, which is more expressed in the western world. These patient groups cannot sit in a wheelchair for the rest of their life, as research indicates that sitting in a wheelchair may shorten life expectancy of these patient groups. A prosthetic limb is complicated and has to be adjusted and personalized for individuals and it should fit the individual’s age, body shape and activity level. In addition to solving technical challenges, participatory and emphatic approaches are needed when technicians collaborate with amputated patients. Today, clinical centers are processing most of this information manually and there is no systematic way to treat these types of patients based on their sensory inputs and values measured in real time. To the best of our knowledge, there is no existing system that motivates the patients to improve their progress in “real time”. At the same time, there is no system that lets the health personnel to know the effectiveness of their rehabilitation practice for a specific patient.
Furthermore, many LLAs who are prosthetic users may have major challenges in relation to their gait. This may be due to several different factors. A major cause is related to that LLA patients do not have the muscle control of the prosthesis, and that there is a lack of proprioceptive information to the nervous system of the foot complex joint and muscle system, which constantly adapts the foot to the ground. In addition, there is no sensory feedback from the sole of the foot. Consequently, the LLA patients have a reduced balance control, when standing and walking. Furthermore, LLA may affect a number of parameters such as, inter alia, the duration of the swing phase, and stride are often shortened, for the amputated side compared with a healthy side. Thus, persons with LLA may often experience disturbances both during walking and when standing still. This is especially pronounced when the terrain is challenging, and when they try to avoid various physical obstacles, which can cause an increased risk of falls and injuries. However, it is widely known among rehabilitation professionals that many prosthetic users are highly dependent on good vision to adjust and compensate for the prosthesis’ contact with the ground during walking. If the visual sensory is attenuated, it may cause unstable walking function for these patient groups. The situation is less pronounced in non-amputated people but may be one of the components for the fall of elderly in particular at home when the light intensity is reduced. As shown in figure 1, several parameters have to be measured in order to estimate the rehabilitation progress.
Figure 1. Illustrating the complexity of how a rehabilitation process is structured and how a personalized and optimized rehabilitation can be structured.