scholarly journals The Validity of a Mixed Reality-Based Automated Functional Mobility Assessment

2019 ◽  
Author(s):  
Ruopeng Sun ◽  
Roberto G. Aldunate ◽  
Jacob J Sosnoff
Keyword(s):  
Mixed Reality ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Preliminary Investigation ◽  
Functional Mobility ◽  
Timed Up And Go ◽  
Perfect Agreement ◽  
Mobility Performance ◽  
Mobility Assessment ◽  
Kinematic Measures

Functional mobility assessments (i.e., Timed Up and Go) are commonly used clinical tools for mobility and fall risk screening in the aging population. In this work, we proposed a new Mixed Reality (MR)-based assessment that utilized a Microsoft HoloLensTM headset to automatically lead and track the performance of functional mobility tests, and subsequently evaluated its validity in comparison with reference inertial sensors. Twenty-two healthy adults (10 older, 12 young) participated in this study. An automated functional mobility assessment app was developed based on the HoloLens platform. Mobility performance was recorded with the headset built-in sensor and validated with reference inertial sensor (Opal, APDM) taped on the headset and lower back. Results indicate vertical kinematic measures by HoloLens was in good agreement with the reference sensor (Normalized RMSE ~ 10%). Additionally, the HoloLens-based test completion time was in perfect agreement with clinical standard stopwatch measure. Overall, our preliminary investigation indicates that it is possible to use an MR headset to automatically guide users to complete common mobility tests with good measurement accuracy, thus it has great potential to provide objective and efficient sensor-based mobility assessment.

scholarly journals The Validity of a Mixed Reality-Based Automated Functional Mobility Assessment

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2183 ◽  
Author(s):  
Ruopeng Sun ◽  
Roberto G. Aldunate ◽  
Jacob J. Sosnoff
Keyword(s):  
Mixed Reality ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Preliminary Investigation ◽  
Functional Mobility ◽  
Timed Up And Go ◽  
Perfect Agreement ◽  
Mobility Performance ◽  
Mobility Assessment ◽  
Clinical Tools

Functional mobility assessments (i.e., Timed Up and Go) are commonly used clinical tools for mobility and fall risk screening in older adults. In this work, we proposed a new Mixed Reality (MR)-based assessment that utilized a Microsoft HoloLensTM headset to automatically lead and track the performance of functional mobility tests, and subsequently evaluated its validity in comparison with reference inertial sensors. Twenty-two healthy adults (10 older and 12 young adults) participated in this study. An automated functional mobility assessment app was developed, based on the HoloLens platform. The mobility performance was recorded with the headset built-in sensor and reference inertial sensor (Opal, APDM) taped on the headset and lower back. The results indicate that the vertical kinematic measurements by HoloLens were in good agreement with the reference sensor (Normalized RMSE ~ 10%, except for cases where the inertial sensor drift correction was not viable). Additionally, the HoloLens-based test completion time was in perfect agreement with the clinical standard stopwatch measure. Overall, our preliminary investigation indicates that it is possible to use an MR headset to automatically guide users (without severe mobility deficit) to complete common mobility tests, and this approach has the potential to provide an objective and efficient sensor-based mobility assessment that does not require any direct research/clinical oversight.

Coexistent Osteoarthritis and Parkinson’s Disease: Data from the Parkinson’s Foundation Outcomes Project

2020 ◽  
Vol 10 (4) ◽  
pp. 1601-1610
Author(s):  
Jaimie A. Roper ◽  
Abigail C. Schmitt ◽  
Hanzhi Gao ◽  
Ying He ◽  
Samuel Wu ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Study Data ◽  
Functional Mobility ◽  
Quality Improvement Initiative ◽  
Timed Up And Go ◽  
Mobility Performance ◽  
Risk Of Mortality ◽  
The Impact

Background: The impact of concurrent osteoarthritis on mobility and mortality in individuals with Parkinson’s disease is unknown. Objective: We sought to understand to what extent osteoarthritis severity influenced mobility across time and how osteoarthritis severity could affect mortality in individuals with Parkinson’s disease. Methods: In a retrospective observational longitudinal study, data from the Parkinson’s Foundation Quality Improvement Initiative was analyzed. We included 2,274 persons with Parkinson’s disease. The main outcomes were the effects of osteoarthritis severity on functional mobility and mortality. The Timed Up and Go test measured functional mobility performance. Mortality was measured as the osteoarthritis group effect on survival time in years. Results: More individuals with symptomatic osteoarthritis reported at least monthly falls compared to the other groups (14.5% vs. 7.2% without reported osteoarthritis and 8.4% asymptomatic/minimal osteoarthritis, p = 0.0004). The symptomatic group contained significantly more individuals with low functional mobility (TUG≥12 seconds) at baseline (51.5% vs. 29.0% and 36.1%, p < 0.0001). The odds of having low functional mobility for individuals with symptomatic osteoarthritis was 1.63 times compared to those without reported osteoarthritis (p < 0.0004); and was 1.57 times compared to those with asymptomatic/minimal osteoarthritis (p = 0.0026) after controlling pre-specified covariates. Similar results hold at the time of follow-up while changes in functional mobility were not significant across groups, suggesting that osteoarthritis likely does not accelerate the changes in functional mobility across time. Coexisting symptomatic osteoarthritis and Parkinson’s disease seem to additively increase the risk of mortality (p = 0.007). Conclusion: Our results highlight the impact and potential additive effects of symptomatic osteoarthritis in persons with Parkinson’s disease.

THUR 229 Inertial sensors improve traditional gait monitoring in HSP patients

2018 ◽  
Vol 89 (10) ◽  
pp. A33.2-A33
Author(s):  
McNamara Mary ◽  
Segamogaite Ruta ◽  
Shaw Pamela ◽  
McDermott Christopher ◽  
Mazzá Claudia ◽  
...  
Keyword(s):  
Longitudinal Study ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Brief Pain Inventory ◽  
Timed Up And Go ◽  
Mild Disease ◽  
Gait Characteristics ◽  
Gait Monitoring ◽  
Ashworth Score

BackgroundHSP is characterised by spasticity and progressive gait impairment. There’s no reliable way to monitor gait deterioration during clinics. Optoelectronic systems have demonstrated differing characteristics between gait of HSP patients and controls. They’re expensive and impractical for use in clinic settings. Inertial sensors haven’t been used to characterise HSP gaitObjectivesStudy use of inertial sensors to identify gait characteristics that differentiate mild HSP patients from controls. To identify a gait based biomarker which can be used to monitor disease progression in a longitudinal study.MethodsNeurological examination, SPRS, Modified Ashworth score, brief pain inventory were undertaken. Instrumented timed up and go (iTUG) and instrumented 10 metre walk tests (i10) wearing an inertial sensor during clinic appointments at 6 month intervals.ResultsGait variables differentiating between patients and controls, including those with mild disease, were identified. Parameters differentiating between patients with SPG4 and SPG7 mutations were found. 8 patients were re-assessed after 6 months. Analysis did not show gait deterioration.ConclusionInertial sensors can detect differences between HSP patients and controls, including those mildly affected. They can also differentiate between patients with different mutations. Further follow up data is needed to assess whether inertial sensors can predict future gait deterioration.

‘Timed up and go’ and brain atrophy: a preliminary MRI study to assess functional mobility performance in multiple sclerosis

2017 ◽  
Vol 264 (11) ◽  
pp. 2201-2204 ◽  
Author(s):  
Lorena Lorefice ◽  
G. Coghe ◽  
G. Fenu ◽  
M. Porta ◽  
G. Pilloni ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Brain Atrophy ◽  
Functional Mobility ◽  
Timed Up And Go ◽  
Mobility Performance ◽  
Mri Study

scholarly journals Exploration of Fall-Evaluation Scores Using Clinical Tools with the Short-Form Berg Balance Scale and Timed Up and Go and Motion Detection Sensors

2020 ◽  
Vol 10 (19) ◽  
pp. 6931
Author(s):  
Chia-Hsuan Lee ◽  
Chi-Han Wu ◽  
Bernard C. Jiang ◽  
Tien-Lung Sun
Keyword(s):  
Domain Knowledge ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Short Form ◽  
Berg Balance Scale ◽  
Multiscale Entropy ◽  
Clinical Test ◽  
Test Results ◽  
Timed Up And Go ◽  
Clinical Tools

The results obtained by medical experts and inertial sensors via clinical tests to determine fall risks are compared. A clinical test is used to perform the whole timed up and go (TUG) test and segment-based TUG (sTUG) tests, considering various cutoff points. In this paper, (a) t-tests are used to verify fall-risk categorization; and (b) a logistic regression with 100 stepwise iterations is used to divide features into training (80%) and testing sets (20%). The features of (a) and (b) are compared, measuring the similarity of each approach’s decisive features to those of the clinical-test results. In (a), the most significant features are the Y and Z axes, regardless of the segmentation, whereas sTUG outperforms TUG in (b). Comparing the results of (a) and (b) based on the overall TUG test, the Z axis multiscale entropy (MSE) features show significance regardless of the approach: expert opinion or logistic prediction. Among various clinical test combinations, the only commonalities between (a) and (b) are the Y-axis MSE features when walking. Thus, machine learning should be based on both expert domain knowledge and a preliminary analysis with objective screening. Finally, the clinical test results are compared with the inertial sensor results, prompting the proposal for multi-oriented data analysis to objectively verify the sensor results.

scholarly journals The application of principal component analysis to characterize gait and its association with falls in multiple sclerosis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Andrew S. Monaghan ◽  
Jessie M. Huisinga ◽  
Daniel S. Peterson
Keyword(s):  
Multiple Sclerosis ◽  
Principal Component Analysis ◽  
Dynamic Stability ◽  
Fear Of Falling ◽  
Inertial Sensors ◽  
Principal Component ◽  
Component Analysis ◽  
Functional Mobility ◽  
Timed Up And Go ◽  
Trunk Motion

AbstractPeople with multiple sclerosis (PwMS) demonstrate gait impairments that are related to falls. However, redundancy exists when reporting gait outcomes. This study aimed to develop an MS-specific model of gait and examine differences between fallers and non-fallers. 122 people with relapsing–remitting MS and 45 controls performed 3 timed up-and-go trials wearing inertial sensors. 21 gait parameters were entered into a principal component analysis (PCA). The PCA-derived gait domains were compared between MS fallers (MS-F) and MS non-fallers (MS-NF) and correlated to cognitive, clinical, and quality-of-life outcomes. Six distinct gait domains were identified: pace, rhythm, variability, asymmetry, anterior–posterior dynamic stability, and medial–lateral dynamic stability, explaining 79.15% of gait variance. PwMS exhibited a slower pace, larger variability, and increased medial–lateral trunk motion compared to controls (p < 0.05). The pace and asymmetry domains were significantly worse (i.e., slower and asymmetrical) in MS-F than MS-NF (p < 0.001 and p = 0.03, respectively). Fear of falling, cognitive performance, and functional mobility were associated with a slower gait (p < 0.05). This study identified a six-component, MS-specific gait model, demonstrating that PwMS, particularly fallers, exhibit deficits in pace and asymmetry. Findings may help reduce redundancy when reporting gait outcomes and inform interventions targeting specific gait domains.

scholarly journals Evaluation of functional mobility of patients with stroke sequela after treatment in hydrotherapy pool using the Timed Up and Go Test

2011 ◽  
Vol 9 (3) ◽  
pp. 302-306 ◽  
Author(s):  
Daniel Gonçalves dos Santos ◽  
Andréa Sanches Navarro Pegoraro ◽  
Carolina Vilela Abrantes ◽  
Fabio Jakaitis ◽  
Silvia Gusman ◽  
...  
Keyword(s):  
Exercise Program ◽  
Functional Mobility ◽  
Stroke Patients ◽  
Timed Up And Go ◽  
Mobility Performance ◽  
Before And After ◽  
Standing Up ◽  
Therapy Sessions ◽  
Post Therapy

ABSTRACT Objective: To evaluate the functional mobility of patients with stroke over 12 sessions of hydrotherapy. Methods: Ten stroke patients aged between 5 and 85 years were evaluated by means of the Timed Up and Go test, which contains some items, such as balance, walking speed, changing directions, and standing up from a seated position. The study patients performed the test before and after each hydrotherapy session (total of 12 sessions). Each individual was compared to him/ herself both short-term (pre- and post-therapy) and long-term (after 12 therapy sessions). Result: Comparing baseline and after 12 sessions, it was noted that the 10 patients improved their performance, with a decrease in time to execute the Timed Up and Go test. Conclusion: An exercise program in a hydrotherapy pool was beneficial for functional mobility performance improvement in stroke patients.

scholarly journals Effectiveness of exergames for improving mobility and balance in older adults: A systematic review and meta-analysis.

2020 ◽  
Author(s):  
Thaiana Barbosa Ferreira Pacheco ◽  
Candice Simões Pimenta de Medeiros ◽  
Victor Hugo Brito de Oliveira ◽  
Edgar Ramos Vieira ◽  
Fabrícia Azevêdo da Costa Cavalcanti
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Center Of Pressure ◽  
Meta Analysis ◽  
Functional Mobility ◽  
Control Group ◽  
Controlled Trials ◽  
Cochrane Central Register ◽  
Timed Up And Go ◽  
Perfect Agreement

Abstract Background: Exergaming is a fun, engaging, and interactive form of exercising and it may help overcome some of the traditional exercise barriers and help improve adherence by older adults providing therapeutic applications for balance recovery and functional mobility. The purpose of this systematic review is to summarize the effects of exergames in older adults’ mobility and balance. Methods: The PRISMA guidelines for systematic reviews were followed. The following databases were searched from inception to August 2019: Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, PEDro, CINAHL and INSPEC. We selected randomized controlled trials that assessed the effects of exergames on balance or mobility of older adults without neurological conditions, in comparison to no intervention or health education. Two review authors independently screened the trials titles and abstracts and identified trials for inclusion according to the eligibility criteria. Trial selection presented an almost perfect agreement between the authors regarding the interrater reliability (kappa = 0.84; p<0,001). Then, a descriptive analysis of the quantitative data was performed to summarize the evidence. Meta-analysis was carried using Revman. Random effects model was used to compute the pooled prevalence at 95% confidence interval. Results: After screening 822 trials, twelve trials comparing exergames with no intervention were included. A total of 1520 older adults participated in the studies, with mean age of 76±6 years for the experimental group and 76±5 years for the control group. Three studies found significant improvements in balance based on center of pressure sway and Berg Balance Scale scores. Three studies found improved mobility based on the timed up and go, 30-second chair stand, and 8-foot up and go test. Conclusions: Exergames improved balance and mobility in older adults without neurological disorders. High quality studies with standardized assessment protocols are necessary to improve evidence.

scholarly journals Toward a Regulatory Qualification of Real-World Mobility Performance Biomarkers in Parkinson’s Patients Using Digital Mobility Outcomes

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5920
Author(s):  
Marco Viceconti ◽  
Sabina Hernandez Penna ◽  
Wilhelmus Dartee ◽  
Claudia Mazzà ◽  
Brian Caulfield ◽  
...  
Keyword(s):  
Real World ◽  
Inertial Sensors ◽  
Wearable Sensors ◽  
Human Movement ◽  
European Medicines Agency ◽  
Drug Trials ◽  
Mobility Performance ◽  
Mobility Assessment ◽  
Drug Regulatory Agencies ◽  
Wearable Inertial Sensors

Wearable inertial sensors can be used to monitor mobility in real-world settings over extended periods. Although these technologies are widely used in human movement research, they have not yet been qualified by drug regulatory agencies for their use in regulatory drug trials. This is because the first generation of these sensors was unreliable when used on slow-walking subjects. However, intense research in this area is now offering a new generation of algorithms to quantify Digital Mobility Outcomes so accurate they may be considered as biomarkers in regulatory drug trials. This perspective paper summarises the work in the Mobilise-D consortium around the regulatory qualification of the use of wearable sensors to quantify real-world mobility performance in patients affected by Parkinson’s Disease. The paper describes the qualification strategy and both the technical and clinical validation plans, which have recently received highly supportive qualification advice from the European Medicines Agency. The scope is to provide detailed guidance for the preparation of similar qualification submissions to broaden the use of real-world mobility assessment in regulatory drug trials.

scholarly journals Reference in-vitro dataset for inertial-sensor-to-bone alignment applied to the tibiofemoral joint

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ive Weygers ◽  
Manon Kok ◽  
Thomas Seel ◽  
Darshan Shah ◽  
Orçun Taylan ◽  
...  
Keyword(s):  
Inertial Sensors ◽  
Inertial Sensor ◽  
Ground Truth ◽  
Transformation Matrices ◽  
True Model ◽  
Advance Research ◽  
Manual Palpation ◽  
Visualization Tools ◽  
Inertial Measurements

AbstractSkin-attached inertial sensors are increasingly used for kinematic analysis. However, their ability to measure outside-lab can only be exploited after correctly aligning the sensor axes with the underlying anatomical axes. Emerging model-based inertial-sensor-to-bone alignment methods relate inertial measurements with a model of the joint to overcome calibration movements and sensor placement assumptions. It is unclear how good such alignment methods can identify the anatomical axes. Any misalignment results in kinematic cross-talk errors, which makes model validation and the interpretation of the resulting kinematics measurements challenging. This study provides an anatomically correct ground-truth reference dataset from dynamic motions on a cadaver. In contrast with existing references, this enables a true model evaluation that overcomes influences from soft-tissue artifacts, orientation and manual palpation errors. This dataset comprises extensive dynamic movements that are recorded with multimodal measurements including trajectories of optical and virtual (via computed tomography) anatomical markers, reference kinematics, inertial measurements, transformation matrices and visualization tools. The dataset can be used either as a ground-truth reference or to advance research in inertial-sensor-to-bone-alignment.

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