Motion analysis made simple and reliable.

3D Cameras

We work with sensors that scan their environment three-dimensionally using infrared light analysis and are able to accurately measure shapes and movements in the space in front of them. With such commercially available 3D cameras, body parts can be tracked with an accuracy in the millimeter range - without requiring the user to wear any markers or special clothing.

What we measure

For each motor task, specific kinematic outcome parameters were developed to describe motor behavior and symptoms. These parameters are in metrical units and therefore easily interpreted by a trained professional. We additionally provide analysis modules that use computer vision approaches to generate and aggregate visualizations of depth videos, such as motion profiles. This can be used for validation of recordings or exploratory evaluation of movement patterns.

For each motor task, kinematic parameters are extracted describing different motor symptoms.

  • Alt Tag

    Sway range and velocity in pitch, roll and 3D, Romberg ratios

    Postural stability is decreased in mild cases of MS compared to HC

    Behrens et al: „Validity of visual perceptive computing for static posturography in patients with multiple sclerosis“. Multiple Sclerosis Journal 2016.

  • Alt Tag

    Speed, step length, torso range of motion

    Gait speed is an established vital indicator of risk of falling

    Grobelny et al: “Maximum walking speed in multiple sclerosis assessed with visual perceptive computing“. PLOS ONE 2017.

  • Alt Tag

    Knee range of motion, cadence, asymmetry, arrhythmicity

    Assessment of e.g. bradykinesia, detection of freezing of gait in PD

    Otte et al: “Instrumental Measurement of Stepping in Place - Detection of Asymmetry and Freezing of Gait“. Movement Disorder Congress 2017.

Accurate, Reliable and Validated

All our kinematic outcomes are clinically and technically validated against gold standard methods and provide a high reliability. For each parameter, individual accuracy levels are given to understand where and when to use them. Our outcomes are evaluated and used in clinical studies, published in peer-reviewed journals and presented at international congresses since 2014.


Peer reviewed papers:

  • Steinert, A.; Sattler, I.; Otte, K.; Röhling, H.; Mansow-Model, S.; Müller-Werdan, U. Using New Camera-Based Technologies for Gait Analysis in Older Adults in Comparison to the Established GAITRite System. Sensors 2020, 20, 125. [PubMed] [DOI]
  • Kroneberg D, Elshehabi M, Meyer A-C, Otte K, Doss S, Paul F, Nussbaum S, Berg D, Kühn AA, Maetzler W and Schmitz-Hübsch T (2019) Less Is More – Estimation of the Number of Strides Required to Assess Gait Variability in Spatially Confined Settings. Front. Aging Neurosci. 10:435. [PubMed] [DOI]
More publications…

Conference posters and talks:

  • Otte, Karen; Röhling, Hanna; Rasche, Ludwig; Ellermeyer, Tobias; Mansow-Model, Sebastian; Paul, Friedemann; Brandt, Alexander U; Lipp, Axel; Schmitz-Hübsch, Tanja; 2019. Quantitative analysis of MDS-UPDRS III finger tapping and hand grip test using visual perceptive computing.
  • Otte, K., Heinrich, F., Ellermeyer, T., Kayser, B., Mansow-Model, S., Paul, F., Brandt, A.U., Skowronek, C., Lipp, A., Schmitz-Hübsch, T., 2018. Evaluation of visual perceptive computing for Tremor Analysis. Mov Disord. 33 (suppl 2), 1.
More posters and talks…