Visuo-perzeptive Bewegungsanalyse von Patienten mit Multipler Sklerose

Hintergrund: Gangstörungen bei Personen mit Multipler Sklerose (PmMS) sind häufig, die detaillierte Beurteilung dieser in Forschung und ambulanter Versorgung jedoch ist anspruchsvoll. Vorherige Studien zeigten Validität und Umsetzbarkeit visuo-perzeptiver Ganganalysen bei PmMS. Unter anderem wurde der Short Maximum Speed Walk (SMSW) eingeführt, mit dem das Gangbild auf einer sehr kurzen Messstrecke beurteilt werden kann. Ziel: Die Äquivalenz des SMSW im Vergleich zum Untersucher-abhängigen Timed 25-Foot Walk (T25FW) in einer großen Kohorte von PmMS zu prüfen. Es sollte zudem die Assoziation der aus dem SMSW abgeleiteten Gangparameter mit dem Grad der Behinderung sowie mit der subjektiven Beeinträchtigung des Gangbildes untersucht werden, um den SMSW als schnelle und objektive Messmethode mit klinischer Relevanz und als dem T25FW womöglich überlegen zu validieren. Methoden: 95 PmMS und 60 gesunde Kontrollen (GK) führten pro Person jeweils drei Messungen des SMSW mittels visuo-perzeptiver Bewegungsanalyse mit der Microsoft® Kinect™ durch, um die Test-Retest-Reliabilität zu ermitteln. Beide Gruppen absolvierten ebenfalls den T25FW. Der Behinderungsgrad der PmMS wurde anhand der Expanded Disability Status Scale (EDSS) und die selbst wahrgenommene Gangbeeinträchtigung mit der 12-item Multiple Sclerosis Walking Scale (MSWS-12) beurteilt. Ergebnisse: PmMS zeigten während des SMSW eine geringere mittlere Geschwindigkeit (p < 0,001) und größere mediolaterale Deviation (p = 0,002) als GK. Die mittlere Geschwindigkeit war der SMSW Parameter mit der höchsten Reliabilität in beiden Gruppen (Intraklassen-Korrelationskoeffizient (ICC) bei PmMS = 0,985 und bei GK = 0,977). Die mittlere Geschwindigkeit sank mit dem Alter bei PmMS und GK (r bei PmMS = -0,648 und bei GK = -0,452, jeweils p < 0,001). Die Korrelation zwischen der mittleren Geschwindigkeit im SMSW und der im T25FW war in beiden Gruppen hoch (r bei PmMS = 0,783 und bei GK = 0,747, jeweils p < 0,001) und die mittlere Differenz (0,0013 m/s) zwischen den Methoden lag unter der kleinsten erkennbaren Änderung. Die mittlere Geschwindigkeit korrelierte gut mit der klinischen Behinderung basierend auf dem EDSS (r = -0,586, p < 0,001) und mit der selbst wahrgenommenen Gangbeeinträchtigung basierend auf der MSWS-12 (r = -0,546, p < 0,001). Schlussfolgerung: Gangparameter der visuo-perzeptiven Bewegungsanalyse während des SMSW können Gangstörungen bei PmMS zuverlässig auf sehr kurzen Strecken erkennen. Insbesondere die maximale Gehgeschwindigkeit kann in diesem simplen Testaufbau mit hoher Genauigkeit bestimmt werden. Assoziationen mit Behinderung und selbst wahrgenommener Gangbeeinträchtigung untermauern die klinische Relevanz. Weitere Forschung ist notwendig, jedoch ist der SMSW aufgrund der Objektivität in einem simplen Testaufbau dem T25FW potentiell überlegen.Gait is often impaired in people with multiple sclerosis (PwMS), but detailed assessment of gait impairment in research and care remains challenging. In previous studies the validity and feasibility of visual perceptive computing (VPC) for objective gait assessments in PwMS was shown. Among these, the Short Maximum Speed Walk (SMSW) was introduced, which assesses gait on very short recording distances. Objective: To investigate the equivalence of SMSW to rater-based Timed 25-Foot Walk in a large cohort of PwMS. Additionally, the association of SMSW-derived gait parameters with clinical disability as well as subjective gait impairment should be investigated, in order to validate the SMSW as a quick and objective measure of clinical relevance possibly superior to T25FW. Methods: 95 PwMS and 60 healthy controls (HC) each absolved three measurements of the SMSW using a VPC system with the Microsoft® Kinect™ in order to establish testretest- reliability. Both groups also performed the T25FW. In PwMS, disability was rated according to the Expanded Disability Status Scale (EDSS) and self-perceived walking impairment according to the 12-item Multiple Sclerosis Walking Scale (MSWS-12). Results: PwMS showed reduced average speed (p < 0.001) and higher mediolateral deviation (p = 0.002) during SMSW than HC. Average speed was the most reliable SMSW parameter in both groups (intra-class correlation coefficient (ICC) in PwMS = 0.985, and in HC = 0.977). Average speed declined with age in PwMS and HC (r in PwMS = -0.648, and in HC = -0.452, both p < 0.001). Correlation of SMSW average speed and T25FW speed was high in both groups (r in PwMS = 0.783, and in HC = 0.747, both p < 0.001) and the mean difference (0.0013 m/s) between both methods was below the smallest detectable change. Average speed correlated well with both clinical disability based on EDSS (r = -0.586, p < 0.001) and self-perceived walking impairment based on MSWS-12 (r = -0.546, p < 0.001). Conclusion: VPC-assessed walking parameters during SMSW can reliably detect gait disturbance in PwMS over very short distance. Specifically, maximum gait speed can be obtained with high accuracy in this simple test set-up. Associations with disability and self-perceived walking impairment support clinical relevance. Future research is needed but given its objectivity in a simple test set-up, SMSW is possibly superior to T25FW

Subjective and objective assessment of physical activity in multiple sclerosis and their relation to health-related quality of life

Background Physical activity (PA) is frequently restricted in people with multiple sclerosis (PwMS) and aiming to enhance PA is considered beneficial in this population. We here aimed to explore two standard methods (subjective plus objective) to assess PA reduction in PwMS and to describe the relation of PA to health-related quality of life (hrQoL). Methods PA was objectively measured over a 7-day period in 26 PwMS (EDSS 1.5–6.0) and 30 matched healthy controls (HC) using SenseWear mini® armband (SWAmini) and reported as step count, mean total and activity related energy expenditure (EE) as well as time spent in PA of different intensities. Measures of EE were also derived from self-assessment with IPAQ (International Physical Activity Questionnaire) long version, which additionally yielded information on the context of PA and a classification into subjects’ PA levels. To explore the convergence between both types of assessment, IPAQ categories (low, moderate, high) were related to selected PA parameters from objective assessment using ANOVA. Group differences and associated effect sizes for all PA parameters as well as their relation to clinical and hrQoL measures were determined. Results Both, SWAmini and IPAQ assessment, captured differences in PA between PwMS and HC. IPAQ categories fit well with common cut-offs for step count (p = 0.002) and mean METs (p = 0.004) to determine PA levels with objective devices. Correlations between specifically matched pairs of IPAQ and SWAmini parameters ranged between r .288 and r .507. Concerning hrQoL, the lower limb mobility subscore was related to four PA measures, while a relation with patients’ report of general contentment was only seen for one. Conclusions Both methods of assessment seem applicable in PwMS and able to describe reductions in daily PA at group level. Whether they can be used to track individual effects of interventions to enhance PA levels needs further exploration. The relation of PA measures with hrQoL seen with lower limb mobility suggests lower limb function not only as a major target for intervention to increase PA but also as a possible surrogate for PA changes

Numerical Analyses of Transient Combustion Process by Using the Lagrangian Discrete Droplet Method

Correlations between SWAmini parameters. (DOCX 13 kb

Maximum walking speed in multiple sclerosis assessed with visual perceptive computing

<div><p>Background</p><p>Gait is often impaired in people with multiple sclerosis (PwMS), but detailed assessment of gait impairment in research and care remains challenging. In a previous pilot study we reported the feasibility of visual perceptive computing (VPC) for gait assessment in PwMS using the Short Maximum Speed Walk (SMSW), which assesses gait on recording distances confined to less than 4 meters.</p><p>Objective</p><p>To investigate the equivalence of SMSW to rater-based timed 25ft. walk (T25FW) in a large cohort of PwMS, and to investigate the association of SMSW-derived gait parameters with clinical disability, as well as subjective and objective gait impairment, in order to validate the SMSW as a quick and objective measure of clinical relevance possibly superior to T25FW.</p><p>Methods</p><p>95 PwMS and 60 healthy controls (HC) performed the SMSW using a VPC system with Microsoft Kinect. All participants received two immediate retests to establish test-retest-reliability. Both PwMS and HC performed the T25FW. PwMS were rated according to the Expanded Disability Status Scale (EDSS) and answered the 12-item Multiple Sclerosis Walking Scale (MSWS-12) as a measure of self-perceived walking impairment.</p><p>Results</p><p>PwMS showed reduced average speed (p<0.001) and higher mediolateral deviation (p = 0.002) during SMSW than HC. Average speed was the most reliable SMSW parameter in PwMS and HC (intra-class correlation coefficient (ICC) in PwMS = 0.985, and in HC = 0.977). Average speed declined with age in PwMS and HC (r in PwMS = -0.648, and in HC = -0.452, both p<0.001). Correlation of SMSW average speed and T25FW speed was high in both groups (r in PwMS = 0.783, and in HC = 0.747, both p<0.001) and mean difference (0.0013 m/s) between methods was below smallest detectable change. Average speed correlated well with both clinical disability based on EDSS (r = -0.586, p<0.001) and self-perceived walking impairment based on MSWS-12 (r = -0.546, p<0.001).</p><p>Conclusion</p><p>VPC-assessed walking parameters during SMSW can reliably detect gait disturbance in PwMS over very short distance. Specifically, maximum gait speed can be obtained with high accuracy in this simple test set-up. Cross-sectional associations with disability and self-perceived walking impairment support clinical relevance. Given its objectivity in a simple test set-up, SMSW is superior to T25FW.</p></div

Test set-up.

<p>Test set-up.</p

Group differences between PwMS and HC.

<p>Group differences between PwMS and HC.</p

SMSW parameter overview.

<p>SMSW parameter overview.</p

Bland-Altman plot of the differences between SMSW average speed and T25FW speed.

<p>Mean difference (solid line) and limits of confidence (dashed lines) refer to the whole dataset. For better interpretation, HC are rendered as open circles and PwMS as filled circles. In two HC and two PwMS, the difference between both maximum speeds was outside the limits of agreement. All four showed an overestimation of T25FW versus SMSW average speed but did not have any other specific feature in common.</p