An amputation, paralysis, an accident or a stroke can all cause their own deviations in gait patterns. A gait analysis can help researchers and therapists to understand why a person walks in a certain way and help to determine which treatment will be the most effective for that specific person.
RRD has its own specialised movement lab where, with the help of equipment such as 3D infrared cameras, EMG equipment and force plates, we can make measurements for the purpose of scientific research or clinical decisions.
Ambulant measurement method
In addition, we have developed an ambulant measurement method that we can take to any desired location to register and analyse the movements of people during daily activities. With the help of accelerometers, gyroscopes, magnetometers, EMG, advanced algorithms and data fusion, we determine the movements of limbs and the forces that are generated on the body during the movement.
New research area
With this approach, we can produce movement data from gait patterns with the same precision as in our movement lab while being on-site. Furthermore, we will expand this ambulant measurement method with data about the forces under the soles, and we will use it in a wider variety of populations. With ambulant sensors, we are opening up a new research area in the field of biomechanics and motor control and we are obtaining new knowledge about deviant behaviour of the motor system during everyday activities, both simple and complex.
We have a considerable amount of experience with post-stroke patients, people with amputations and children with spastic muscles due to brain disorders. Furthermore, we are increasingly focusing on other groups such as athletes or frail elderly people. In the last group, we are mainly studying balance in the context of preventing falls.
Jasper is a human movement scientist (VU Amsterdam 2002) who holds a PhD in biomechanical engineering (UT 2009). The focus of his research is on the analysis of human movement (from a kinetic, kinematic and exercise physiological perspective) in the field of physical rehabilitation and sports. Central themes are individual movement patterns, the effects of fatigue on movement patterns in relation to injury development (in particular during running) and measuring, monitoring and (re-training) kinematics outside the laboratory by means of inertial magnetic measurement units. Jasper teaches in the Master’s program of Biomedical Engineering at the University of Twente. In the 2015 fall semester Jasper was a Fulbright scholar (visiting professor) at the University of Kentucky, College of Health Science in the BioMotion lab where he studied analysis of movement in rehabilitation and sports.
Gait analysis, Running mechanics, Lower limb injuries, Fatigue, Monitoring and feedback, Inertial sensors, Biomechanics, Exercise Physiology, Gait disorders, Gait (re-)training.
Reenalda J, Maartens E, Buurke JH, Gruber AH (2019). Kinematics and shock attenuation during a prolonged run on the athletic track as measured with inertial magnetic measurement units. Gait & Posture, 68, 155-160. https://doi.org/10.1016/j.gaitpost.2018.11.020
Wouda FJ, Giuberti M, Bellusci G, Maartens E, Reenalda J, van Beijnum BF, Veltink PH (2018). Estimation of Vertical Ground Reaction Forces and Sagittal Knee Kinematics During Running Using Three Inertial Sensors. Frontiers in Physiology, 9, 218. https://doi.org/10.3389/fphys.2018.00218
Reenalda J, Maartens E, Homan L, Buurke JH (2016). Continuous three dimensional analysis of running mechanics during a marathon by means of inertial magnetic measurement units to objectify changes in running mechanics. Journal of Biomechanics, 49(14), 3362-3367. https://doi.org/10.1016/j.jbiomech.2016.08.032
Reenalda J, Maas MTF, de Koning JJ. The influence of added mass on the optimal step length in running. International Journal of Sport Physiology and Performance, 11(7), 920-926. https://doi.org/10.1123/ijspp.2015-0182
Haarman, Reenalda et al (2016). The effect of ‘device-in-charge’ versus ‘patient-in-charge’ support during robotic gait training on walking ability and balance in chronic stroke survivors: a systematic review. Journal of Rehabilitation and Assistive Technologies Engineering, 3, 1-16. https://doi.org/10.1177/2055668316676785.
Jaap received his PhD in 2005 from the University of Twente for his work on recovery of gait after stroke. He is coordinator of the Research Track Rehabilitation Technology at Roessingh Research and Development, adjunct professor at Northwestern University Chicago (USA), senior researcher at Roessingh, Centre for Rehabilitation and affiliated to the biomedical signals and systems group of the University of Twente.
Since 2011 Jaap is president of the Dutch society for neurorehabilitation “Neurorevalidatie-Keypoint” and a member of the Dutch expert group on Neurorehabilitation. He is specialised on human movement analysis with specific expertise in kinesiology (neuromuscular control and biomechanics) after stroke. He is actively involved in a diversity of (inter)national projects focusing on motor control, movement analysis, rehabilitation robotics and active assistive devices.
Nijenhuis SM, Prange-Lasonder GB, Stienen AHA, Rietman JS, Buurke JH (2017). Effects of training with a passive hand orthosis and games at home in chronic stroke: a pilot randomised controlled trial. Clinical Rehabilitation, 31(2), 207-216. https://doi.org/10.1177/0269215516629722
Tenniglo MJB, Nederhand MJ, Prinsen EC, Nene AV, Rietman JS, Buurke JH (2014). Effect of chemodenervation of the rectus femoris muscle in adults with a stiff knee gait due to spastic paresis: a systematic review with a meta-analysis in patients with stroke. Archives of Physical Medicine and Rehabilitation, 95(3), 576-587. https://doi.org/10.1016/j.apmr.2013.11.008
Dubbeldam R, Nester C, Nene AV, Hermens HJ, Buurke JH (2013). Kinematic coupling relationships exist between non-adjacent segments of the foot and ankle of healthy subjects. Gait & Posture, 37(2), 159-164. https://doi.org/10.1016/j.gaitpost.2012.06.033
Renzenbrink GJ, Buurke JH, Nene AV, Geurts AC, Kwakkel G, Rietman JS (2012). Improving walking capacity by surgical correction of equinovarus foot deformity in adult patients with stroke or traumatic brain injury: a systematic review. Journal of Rehabilitation Medicine, 44(8), 614-23. https://doi.org/10.2340/16501977-1012
Buurke JH, Nene AV, Kwakkel G, Erren-Wolters V, IJzerman MJ, Hermens HJ (2008). Recovery of Gait After Stroke: What Changes? Neurorehabilitation and Neural Repair, 22, 676-683. https://doi.org/10.1177/1545968308317972
Chris is senior researcher ‘Ambulatory Movement Analysis’ (Ir. Electrical Engineering with extensions Biomedical Technology / Mathematics Teaching (University of Twente, 1990). At RRD he initiated the research line ‘Ambulatory 3D Analysis of Human Movement’. This line focuses on measuring, analyzing and interpreting human posture, movement, muscle activity and external and internal forces and moments. In many applications these data are interpreted in the context of the underlying (automatically recognized) pattern of activity, especially in long or unsupervised measurements.
All this is aimed at developing support for clinical decision-making by linking the behavior of (electro) -physiological signals and the influence of measuring instruments and analytical methods to biomechanical and clinical insights. Key technologies used include: wearable sensing, data fusion, stochastic signal analysis and machine learning. All activity is focused on the ultimate development of practically useful instruments for the domain professional: the clinician or therapist, but also the sports coach or the ergonomist.
Pioneer work in the field of wearable motion sensing resulted in the 90’s in one of the first 3D inertial motion sensor systems worldwide. Starting from the start of this century this sensor system has been made into a commercial success by the University of Twente startup Xsens Technologies in application areas such as gaming and film production and robot and drone control.
However, developing successful routine applications for clinical decision-making based on wearable sensing technology has proven to be a formidable challenge until the day of today. The ambition to achieve this is central to the current mission of the research line ‘Ambulatory 3D Analysis of Human Movement’.
Chris Baten was and has been involved in many (inter-) national projects and dozens of scientific publications a dozen of PhD supervisions. In the Netherlands, intensive collaboration exists with partners University of Twente, Xsens, Saxion, VU Amsterdam and TU Delft. He was Chair and Scientific Chair of ‘3DMA-08’, the international scientific conference on ‘3D Analysis of Human Movement’ that took place in October 2008 in Amsterdam. He was also President and Member-at-Large of 3DAHM, the International Society of Biomechanics ‘Section on 3D Analysis of Human Movement’. He is an afiliated researcher at the University of Twente and Saxion University.
Areas of Interest
Methods of applied (ambulatory) motion analysis in rehabilitation, physiotherapy, sports and ergonomics, wearable sensor technology, data fusion, biomechanics, electrophysiology, machine learning, stochastic signal analysis.
Baten CTM, van der Aa R,Verkuyl A. ‘Effect of wearable trunk supportfor working in sustained stooped posture on low back net extension moments.’, ISB 2015 – Motion Analysis – ISB 2015-1309 – Glasgow, 2015.
de Vries W, ‘Estimation of the mechanical loading of the shoulder joint in daily conditions’, Dissertation TU Delft, plus onderliggende artikelen, 2015.
Weenk D. ‘Click-on-and-Play Human Motion Capture using Wearable Sensors’, Dissertation University of Twente. CTIT Ph.D. thesis Series No. 15-377 ISBN 978-90-365-3972-2 plus onderliggende artikelen, 2015.
Baten CTM, Klein Horsman M, de Vries W, Koopman B, van der Helm F, Veltink PH. ‘Accurate estimation of body segment kinematics from inertial sensor kinematics’, ISEK 2004, Boston, MA, USA, 2004.
Baten CTM. ‘Ambulatory low back load exposure estimation.’ In Proc. IEA 2000, San Diego, USA, 2000.
Baten CTM, Hamberg HJ, Veltink PH. SAIBLE: ‘A system for functional low back load evaluation in the field combining EMG and movement sensor data using an artificial neural network for system calibration.’ In proc. PREMUS 95, Quebec, Canada, 1995.
Link to Google Scholar