Using perceptive computing in multiple sclerosis - the Short Maximum Speed Walk test

BACKGROUND: We investigated the applicability and feasibility of perceptive computing assisted gait analysis in multiple sclerosis (MS) patients using Microsoft Kinect. To detect the maximum walking speed and the degree of spatial sway, we established a computerized and observer-independent measure, which we named Short Maximum Speed Walk (SMSW), and compared it to established clinical measures of gait disability in MS, namely the Expanded Disability Status Scale (EDSS) and the Timed 25-Foot Walk (T25FW). METHODS: Cross-sectional study of 22 MS patients (age mean +/- SD 43 +/- 9 years, 13 female) and 22 age and gender matched healthy control subjects (HC) (age 37 +/- 11 years, 13 female). The disability level of each MS patient was graded using the EDSS (median 3.0, range 0.0-6.0). All subjects then performed the SMSW and the Timed 25-Foot Walk (T25FW). The SMSW comprised five gait parameters, which together assessed average walking speed and gait stability in different dimensions (left/right, up/down and 3D deviation). RESULTS: SMSW average walking speed was slower in MS patients (1.6 +/- 0.3 m/sec) than in HC (1.8 +/- 0.4 m/sec) (p = 0.005) and correlated well with EDSS (Spearman's Rho 0.676, p < 0.001). Furthermore, SMSW revealed higher left/right deviation in MS patients compared to HC. SMSW showed high recognition quality and retest-reliability (covariance 0.13 m/sec, ICC 0.965, p < 0.001). There was a significant correlation between SMSW average walking speed and T25FW (Pearson's R = -0.447, p = 0.042). CONCLUSION: Our data suggest that ambulation tests using Microsoft Kinect are feasible, well tolerated and can detect clinical gait disturbances in patients with MS. The retest-reliability was on par with the T25FW

Motor signature of autism spectrum disorder in adults without intellectual impairment

Motor signs such as dyspraxia and abnormal gait are characteristic features of autism spectrum disorder (ASD). However, motor behavior in adults with ASD has scarcely been quantitatively characterized. In this pilot study, we aim to quantitatively examine motor signature of adults with ASD without intellectual impairment using marker-less visual-perceptive motion capture. 82 individuals (37 ASD and 45 healthy controls, HC) with an IQ > 85 and aged 18 to 65 years performed nine movement tasks and were filmed by a 3D-infrared camera. Anatomical models were quantified via custom-made software and resulting kinematic parameters were compared between individuals with ASD and HCs. Furthermore, the association between specific motor behaviour and severity of autistic symptoms (Autism Diagnostic Observation Schedule 2, Autism Spectrum Quotient) was explored. Adults with ASD showed a greater mediolateral deviation while walking, greater sway during normal, tandem and single leg stance, a reduced walking speed and cadence, a greater arrhythmicity during jumping jack tasks and an impaired manual dexterity during finger tapping tasks (p  0.48) compared to HC. Furthermore, in the ASD group, some of these parameters correlated moderately to severity of ASD symptoms. Adults with ASD seem to display a specific motor signature in this disorder affecting movement timing and aspects of balance. The data appear to reinforce knowledge about motor signs reported in children and adolescents with ASD. Also, quantitative motor assessment via visual-perceptive computing may be a feasible instrument to detect subtle motor signs in ASD and perhaps suitable in the diagnosis of ASD in the future

Camera-based objective measures of Parkinson's disease gait features

OBJECTIVE: Parkinson's disease is a common, age-related, neurodegenerative disease, affecting gait and other motor functions. Technological developments in consumer imaging are starting to provide high-quality, affordable tools for home-based diagnosis and monitoring. This pilot study aims to investigate whether a consumer depth camera can capture changes in gait features of Parkinson's patients. The dataset consisted of 19 patients (tested in both a practically defined OFF phase and ON phase) and 8 controls, who performed the "Timed-Up-and-Go" test multiple times while being recorded with the Microsoft Kinect V2 sensor. Camera-derived features were step length, average walking speed and mediolateral sway. Motor signs were assessed clinically using the Movement Disorder Society Unified Parkinson's Disease Rating Scale. RESULTS: We found significant group differences between patients and controls for step length and average walking speed, showing the ability to detect Parkinson's features. However, there were no differences between the ON and OFF medication state, so further developments are needed to allow for detection of small intra-individual changes in symptom severity

Cultural bias in motor function patterns: potential relevance for predictive, preventive, and personalized medicine

BACKGROUND: Quantification of motor performance has a promising role in personalized medicine by diagnosing and monitoring, e.g. neurodegenerative diseases or health problems related to aging. New motion assessment technologies can evolve into patient-centered eHealth applications on a global scale to support personalized healthcare as well as treatment of disease. However, uncertainty remains on the limits of generalizability of such data, which is relevant specifically for preventive or predictive applications, using normative datasets to screen for incipient disease manifestations or indicators of individual risks. OBJECTIVE: This study explored differences between healthy German and Japanese adults in the performance of a short set of six motor tests. METHODS: Six motor tasks related to gait and balance were recorded with a validated 3D camera system. Twenty-five healthy adults from Chiba, Japan, participated in this study and were matched for age, sex, and BMI to a sample of 25 healthy adults from Berlin, Germany. Recordings used the same technical setup and standard instructions and were supervised by the same experienced operator. Differences in motor performance were analyzed using multiple linear regressions models, adjusted for differences in body stature. RSEULTS: From 23 presented parameters, five showed group-related differences after adjustment for height and weight (R2 between .19 and .46, p.5) for performance of short comfortable and maximum speed walks. For results of posturography, regression models did not reveal effects of group or body stature. CONCLUSIONS: Our results support the existence of a population-specific bias in motor function patterns in young healthy adults. This needs to be considered when motor function is assessed and used for clinical decisions, especially for personalized predictive and preventive medical purposes. The bias affected only the performance of specific items and parameters and is not fully explained by population-specific ethnic differences in body stature. It may be partially explained as cultural bias related to motor habits. Observed effects were small but are expected to be larger in a non-controlled cross-cultural application of motion assessment technologies with relevance for related algorithms that are being developed and used for data processing. In sum, the interpretation of individual data should be related to appropriate population-specific or even better personalized normative values to yield its full potential and avoid misinterpretation

Validity of visual perceptive computing for static posturography in patients with multiple sclerosis

Background: Multiple sclerosis (MS) patients frequently have postural control impairment but quantitative posturography is difficult to perform in clinical care. Recent technology facilitates new posturography approaches. Objective: To evaluate construct validity of visual perceptive computing (VPC) for static posturography to study postural control in MS patients. Methods: A total of 90 MS patients and 59 healthy controls (HCs) performed three stance tests: open, closed and tandem stance. Static posturography was performed using a VPC system with Microsoft Kinect. Clinical assessments included Expanded Disability Status Scale (EDSS), Timed-25-Foot-Walk, Short-Maximum-Speed-Walk and 12-item MS Walking Scale (MSWS-12) questionnaire. Reliability was assessed with intra-class correlation coefficients at retest. Results: As a group, MS patients performed worse than HCs in all tests. The closed stance test showed best applicability and reliability. With closed eyes, in 36.7% of patients, the three-dimensional mean angular sway velocity (MSV-3D) was above HCs’ 95th percentile. Higher MSV-3D was associated with decreased walking speed (p < 0.001); worse clinical scores, mainly attributable to the cerebellar functional system score (p < 0.001); and reflected in self-reported walking disability (MSWS-12, p < 0.001). Conclusion: Postural control can be reliably assessed by VPC-based static posturography in patients with MS. Abnormal postural control seems to predominantly reflect involvement of cerebellar circuits with impact on gait and walking disability