Identifying car ingress movement strategies before and after total knee replacement

Dynamic stability during stair negotiation after total knee arthroplasty

BACKGROUND

The assessment of dynamic stability is crucial for the prevention of falls in the elderly and people with functional impairments. Evidence that total knee arthroplasty improves balance in patients with severe osteoarthritis is scarce and no information exists about how the surgery affects dynamic stability during stair negotiation.

METHODS

This study aims to investigate if patients before and one year after surgery are less stable compared to asymptomatic controls. Seventeen control and twenty-seven patient participants with end-stage knee osteoarthritis that were scheduled to undergo unilateral total knee arthroplasty were recruited in this study. Participants' assessment was carried out by means of marker-based optical full-body motion capture with force platforms. The extrapolated Centre of mass and the margin of stability metrics were used to examine dynamic stability during stair ascent and descent.

FINDINGS

Patient participants, during both pre-operative and post-operative assessments, were equally balanced to the asymptomatic controls during stair gait (p > .188). Additionally, the patients' overall stability did not improve significantly one year after arthroplasty surgery (p > .252).

INTERPRETATION

Even if pain from arthritis and fear of falling is decreased following surgery, our results indicate that stability in stair walking in not affected by osteoarthritis and total knee arthroplasty.

CLINICAL TRIAL REGISTRATION NUMBER

NCT02422251.

Implant design affects walking and stair navigation after total knee arthroplasty: a double-blinded randomised controlled trial

BACKGROUND

Dissimilar total knee arthroplasty implant designs offer different functional characteristics. This is the first work in the literature to fully assess the Columbus ultra-congruent mobile (UCR) system with a rotating platform.

METHODS

This is a double-blinded randomised controlled trial, comparing the functional performance of the low congruent fixed (CR DD), ultra-congruent fixed (UC) and UCR Columbus Total Knee Systems. The pre-operative and post-operative functional performance of twenty-four osteoarthritic patients was evaluated against nine control participants when carrying out everyday tasks. Spatiotemporal, kinematic and kinetic gait parameters in walking and stair navigation were extracted by means of motion capture.

RESULTS

The UC implant provided better post-operative function, closely followed by the UCR design. However, both the UC and UCR groups exhibited restricted post-operative sagittal RoM (walking, 52.1 ± 4.4° and 53.2 ± 6.6°, respectively), whilst patients receiving a UCR implant did not show an improvement in their tibiofemoral axial rotation despite the bearing's mobile design (walking, CR DD 13.2 ± 4.6°, UC 15.3 ± 6.7°, UCR 13.5 ± 5.4°). Patients with a CR DD fixed bearing showed a statistically significant post-operative improvement in their sagittal RoM when walking (56.8 ± 4.6°).

CONCLUSION

It was concluded that both ultra-congruent designs in this study, the UC and UCR bearings, showed comparable functional performance and improvement after TKA surgery. The CR DD group showed the most prominent improvement in the sagittal RoM during walking.

TRIAL REGISTRATION

The study is registered under the clinical trial registration number: NCT02422251 . Registered on April 21, 2015.

Motion Capture Technology in Industrial Applications: A Systematic Review

The rapid technological advancements of Industry 4.0 have opened up new vectors for novel industrial processes that require advanced sensing solutions for their realization. Motion capture (MoCap) sensors, such as visual cameras and inertial measurement units (IMUs), are frequently adopted in industrial settings to support solutions in robotics, additive manufacturing, teleworking and human safety. This review synthesizes and evaluates studies investigating the use of MoCap technologies in industry-related research. A search was performed in the Embase, Scopus, Web of Science and Google Scholar. Only studies in English, from 2015 onwards, on primary and secondary industrial applications were considered. The quality of the articles was appraised with the AXIS tool. Studies were categorized based on type of used sensors, beneficiary industry sector, and type of application. Study characteristics, key methods and findings were also summarized. In total, 1682 records were identified, and 59 were included in this review. Twenty-one and 38 studies were assessed as being prone to medium and low risks of bias, respectively. Camera-based sensors and IMUs were used in 40% and 70% of the studies, respectively. Construction (30.5%), robotics (15.3%) and automotive (10.2%) were the most researched industry sectors, whilst health and safety (64.4%) and the improvement of industrial processes or products (17%) were the most targeted applications. Inertial sensors were the first choice for industrial MoCap applications. Camera-based MoCap systems performed better in robotic applications, but camera obstructions caused by workers and machinery was the most challenging issue. Advancements in machine learning algorithms have been shown to increase the capabilities of MoCap systems in applications such as activity and fatigue detection as well as tool condition monitoring and object recognition.