GaitSmart - a sensor system that measures gait kinematics in a clinical setting to the same accuracy as an optical gait lab in 10 minutes and can provide personalised exercises
GaitSmart measures gait kinematics using seven Inertial Measurement Units (IMUs). These are mounted in custom elasticated straps on the pelvis, thigh and calf of each leg and at the base of the spine. The test takes less than 10 minutes and can be done in a home or clinical setting, such as a GP’s office. It is a Medical Device Class 1m, meaning that the measurement accuracy forms part of our device classification.
The entire system is wireless, using Bluetooth communications from the IMUs to a Smart Tablet and internet access to the cloud server. Data is uploaded and results calculated automatically on the cloud server, where it is stored. Data is presented in an easy to understand report, which users and clinicians can view on the Smart tablet or through a web browser. The format is designed to be easy to understand, using simple traffic light coding to identify areas of concern. The video link shows a test being performed, an image of the report and a brief explanation of what the values mean.
The system can be used to measure anyone who can walk, including older people reliant on walking aids.
Over the last 6 years GaitSmart has been used in the IMI APPROACH project. The aim of this large European project was to identify knee OA phenotypes. A total of 297 patients were recruited and monitored at based, 284 at Month 6 and 220 at Month 24. The data has been analysed and compared to radiographic data, functional data and patient reported outcome measures. The first paper published in Rheumatology using the baseline data concluded ‘GaitSmart analysis provides additional information over established OA outcomes. GaitSmart parameters are also associated with the presence of ROA and extent of radiographic severity over demographics and PROMS. These results indicate that GaitSmart may be an additional outcome measure for the evaluation of OA.’ E.M. van Helvoort et al. Relationship between motion, using the GaitSmartTM, and radiographic knee osteoarthritis: an explorative analysis in the IMI-APPROACH cohort. Rheumatology 2020:00:1-10. The analysis comparing baseline and M6 data shows that GaitSmart data ‘are more responsive to detect an actual change in sit-to-stand or walk activity, as compared to commonly used function measures’. E.M. van Helvoort et al. Motion analysis using the GaitSmart system in the IMI-APPROACH cohort. Osteoarthritis and Cartilage Abstract only Volume 29 Supplement 1 S22-S24 April 1st 2021. The analysis also shows pain is a confounding factor when looking at function.
GaitSmart has also been used in a number of studies on hip and knee replacement patients. Pre-op (late stage OA) data and post op data at 6 weeks and 1 year clearly identifies how the joint kinematics alter with OA progression. Roland Zügner et al. Validation of Inertial Measurement Units with Optical tracking system in patients operated with Total Hip Arthroplasty. BMC Musculoskeletal Disorders 2019. Blixt S. Patient-reported Mobility Problems after Total Hip Arthroplasty. Gothenburg University https://gupea.ub.gu.se/handle/2077/45217 2017. Hanly RJ et al. Outpatient 3-D gait analysis one year after THA using a portable IMU system: bone joint j jun 2016, 98-b (supp 11) 1. Rahman J, Tang Q, Monda M, Miles J, McCarthy I. Gait assessment as a functional outcome measure in total knee arthroplasty: a cross sectional study. BMC Musculoskeletal Disorders 2015 16:66
DML has extended the functionality of the system to help patients with rehabilitation. With the drive towards digital healthcare and personalised medicine, this new innovation offers significant advancement in treating more people with common conditions to the same standard.
In this challenge GaitSmart provides objectivity and accuracy in interpreting joint integrity and joint pain. This helps clinicians and patients increase their understanding of what is happening in a patient’s joint. It will improve diagnosis and enable the right treatment pathway to be chosen for patients.
Walking is a load bearing activity and hence exacerbates pain. Patients have different pain thresholds meaning that pain levels are not a good indicator of joint integrity. Moreover, patients can suffer from referred pain, meaning a pain in the spine can manifest itself as a knee pain for example. Gait kinematics however, provide an objective assessment of all movement within the lower limbs from the pelvis down. This clearly identifies how the hip and knee joints move and this data provides differentiation between patients with joint issues and those with other musculoskeletal issues. The data is compared to our extensive database of healthy subjects, so precise deviations from normal can be established. Changes over time can also be quantified to within a degree, due to the accuracy of our system.
The speed and accuracy of our system means that it can be used on all patients seeking treatment.
The report helps individuals and clinicians understand which joints are causing issues and the severity of these issues. The data can also be analysed remotely by clinicians if required.
If the healthcare provider wishes to provide patients with a personalised exercise plan, then this can be provided using the same test procedure but a different protocol. Our trials have shown that the report provides motivation to adhere to exercises, with a corresponding improvement in gait.
Musculoskeletal conditions that affect gait: Arthritis, Joint replacement, frailty and falls.
GaitSmart provides objective data to support a diagnosis and can provided a personalised exercise rehabilitation programme to strengthen muscles to alleviate symptoms.