http://informahealthcare.com/idt ISSN 1748-3107 print/ISSN 1748-3115 online Disabil Rehabil Assist Technol, Early Online: 1–6 ! 2014 Informa UK Ltd. DOI: 10.3109/17483107.2014.888487

RESEARCH PAPER

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Walking with robot assistance: the influence of body weight support on the trunk and pelvis kinematics Eva Swinnen1,2, Jean-Pierre Baeyens3,4, Kristel Knaepen5, Marc Michielsen6, Gerrit Hens1, Ron Clijsen4, Maggie Goossens7, Ronald Buyl8, Romain Meeusen2,5, and Eric Kerckhofs1,2 1

Faculty of Physical Education and Physiotherapy, Rehabilitation Research (RERE), Vrije Universiteit Brussel, Brussels, Belgium, 2Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium, 3Faculty of Physical Education and Physiotherapy, Department of Biometry and Biomechanics (BIOM), Vrije Universiteit Brussel, Brussels, Belgium, 4Physiotherapy, University College Thim van der Laan, Landquart, Switzerland, 5 Faculty of Physical Education and Physiotherapy, Human Physiology (MFYS), Vrije Universiteit Brussel, Brussels, Belgium, 6Jessa Hospital, Rehabilitation Center Sint-Ursula, Herk-de-Stad, Belgium, 7University College Antwerp, Faculty of Applied Engineering Sciences, Antwerp, Belgium, and 8Faculty of Medicine and Pharmacy, Department of Biostatistics and Medical Informatics, Vrije Universiteit Brussel, Brussels, Belgium Abstract

Keywords

Purpose: The goal was to assess in healthy participants the three-dimensional kinematics of the pelvis and the trunk during robot-assisted treadmill walking (RATW) at 0%, 30% and 50% body weight support (BWS), compared with treadmill walking (TW). Methods: 18 healthy participants walked (2 kmph) on a treadmill with and without robot assistance (Lokomat; 60% guidance force; 0%, 30% and 50% BWS). After an acclimatisation period (four minutes), trunk and pelvis kinematics were registered in each condition (Polhemus Libertyä [240 Hz]). The results were analysed using a repeated measures analysis of variance with Bonferroni correction, with the level of suspension as within-subject factor. Results: During RATW with BWS, there were significantly (1) smaller antero-posterior and lateral translations of the trunk and the pelvis; (2) smaller antero-posterior flexion and axial rotation of the trunk; (3) larger lateral flexion of the trunk; and (4) larger antero-posterior tilting of the pelvis compared with TW. Conclusions: There are significant differences in trunk and pelvis kinematics in healthy persons during TW with and without robot assistance. These data are relevant in gait rehabilitation, relating to normal balance regulation. Additional research is recommended to further assess the influence of robot assistance on human gait.

Body weight support, gait, kinematics, pelvis, robot, trunk History Received 30 September 2013 Revised 21 January 2014 Accepted 24 January 2014 Published online 11 February 2014

ä Implications for Rehabilitation  

The trunk and pelvis moves in a different way during walking with robot assistance. The data suggest that the change in movement is due to the robot device and the harness of the suspension system more than due to the level of suspension itself.

Introduction One of the most used robots to assist gait rehabilitation in neurological patients is the Lokomat system, an exoskeleton device fixated around the hips and lower extremities of the patients and used in combination with a body weight support (BWS) system [1,2]. By using a BWS system, the weight of the patient can be compensated to enable early gait rehabilitation before the patients can bear their full body weight [3]. Gait rehabilitation with robot assistance has many benefits compared with conventional gait rehabilitation, where different therapists need to manually assist the limbs of the patients. These benefits include high repeatability of the prescribed motion, high patient safety and assistance by only one therapist [4].

Address for correspondence: Eva Swinnen, Faculty of Physical Education and Physiotherapy, Advanced Rehabilitation Technology and Science (ARTS), Vrije Universiteit Brussel, Laarbeeklaan 103, B-1090 Brussels, Belgium. Tel/Fax: +32-2-4774530. E-mail: [email protected]

Improvements in gait-related outcome measurements have been reported in the literature, but gait- and balance-related outcome measurements are not better using gait rehabilitation robots than conventional gait rehabilitation methods [5–8]. The exact reasons behind this limited efficacy are not known. For some patient groups, e.g. patients with a minimum of trunk control, one possible explanation might be a restriction in the movements of the trunk and pelvis during robot-assisted walking with the use of a BWS system. Consequently, during this type of training, it may be that the trunk control is improperly trained and thus limiting its part in balance during gait. Multiple studies have shown significant changes in the kinematics of the lower extremities by using robot assistance and/or BWS systems [9–13]. Movements of the trunk and pelvis are important in maintaining dynamic body balance during walking, to enable the swaying movement, to avoid excessive movements of the head and to reduce vertical and lateral displacements of the centre of the body mass to save energy [14–16]. Nevertheless, until now, no studies have been performed

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to assess trunk and pelvis kinematics during robot-assisted treadmill walking (RATW) with different levels of BWS. This study is a first pilot study in this domain. We are convinced that studies with healthy people are necessary for future analysis of studies with patients. Moreover, the aim of this study was not to compare the effect of different levels of BWS during robot assisted gait ‘‘between’’ subjects, but ‘‘within’’ subjects. As a majority of the patient groups for which this device was developed, are not able to walk without any support, we first chose healthy people as an experimental group. In that way, we are able to highlight several key points that may be used in future patient studies. The goal of this study was to assess in healthy participants the three-dimensional (3D) kinematics of the pelvis and the trunk during RATW at 0%, 30% and 50% BWS, compared with treadmill walking (TW). In addition, a comparison between the different levels of BWS was performed. The hypothesis was that during RATW with the use of BWS, there would be a restriction in the movements of the pelvis and the trunk due to the fixation of the exoskeleton of the robotic device and the harness of the suspension system.

Methods Participants Participants between 20 and 60 years of age were recruited among the physical and occupational rehabilitation team of the hospital. The exclusion criteria were neurological disorders and/or mention of cognitive disorders, injuries of the lower extremities or back during the previous six months, abnormal range of motion (ROM) of the lower limbs or the trunk and balance problems. All participants filled in a medical and demographic questionnaire to check whether they could participate and if they met the inclusion criteria. After approval, all participants signed an informed consent form. All participants were insured, and the study was approved by the local ethics commission of the university (BUN B1432008499) and the rehabilitation centre (12.11/fys12.02). Materials The robotic device used in this study was the Lokomat (Hocoma AG, Switzerland). This gait rehabilitation robot is an exoskeleton that is fixated around the pelvis and the lower limbs. The mechanical limbs of the Lokomat guide the lower extremities of the person in a prescribed pattern. The Lokomat device is used in combination with a BWS system that compensates part of the weight of the person. The level of guidance force used in this study was kept constant at 60%. This frequently used percentage in clinical practice is comparable to the intensity of TW with 30% BWS [17]. The BWS device of the Lokomat system was used, although the harness was changed to that of the LiteGait MX300 BWS system (Mobility Research, Tempe, AZ) to achieve a proper EMG electrode application on the trunk (these data will be reported in a subsequent publication). The BWS system itself has two suspension points, one on each side of the person in the frontal plane. From each suspension point, two belts, one on the front and one on the back of the person, ensure the suspension. The harness was suspended at four points, two in front and two at the back. The length of the belts used for suspension was standardised at 10 cm between the suspension fork and the top of the head. To assess the kinematics, the Polhemus LibertyÔ (240/16) (Polhemus, Colchester, England, UK), an electromagnetic tracking device, was used. To track the trunk and pelvis kinematics and to determine the gait cycle, six sensors were used. Tracking data

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were obtained at 240 Hz (accuracy of 0.08 cm for position and 0.15 for orientation). Methods Before starting the protocol, the registration of the sensors was tested to exclude interference from surrounding objects. The sensors were placed at the shoes at the level of the left and right calcaneus and on the skin at the left and right anterior superior iliac spine (ASIS), the sacrum and the manubrium sterni. A stylus sensor marked the anatomic positions, in a standing position, of the left and right acromion, processus spinosus of C7 and T8, sacrum and incisura jugularis of the manubrium sterni. A local embedded frame was built for the pelvis, using the positions of the trackers on the left and right ASIS and the sacrum. The same was done for the trunk by means of the sacrum, C7 and sternum markers. The tracker on the manubrium sterni was continuously followed in relation to the embedded frame built by the position of C7, sacrum and manubrium sterni. The raw tracker data obtained during motion were linked to the local frames and processed in a Matlab (The MathWorks, Eindhoven, The Netherlands) environment into finite helical angles expressed in terms of the pelvis or global coordinate system (i.e. in components of the product of the finite helical angle with the direction vector of the finite helical axis). The output data were calculated in a local maxima/minima algorithm (graphical user interface, Matlab). For each variable from each subject, the mean of these maxima and minima was used to calculate the average ROM. Consequently, the ROM in each plane, for each subject in each walking condition was deduced. The outcomes for rotation were as follows: (1) the amount of rotation of the pelvis compared with the position of the pelvis at mid swing, including antero-posterior tilting (in the sagittal plane, around the transverse axis), lateral tilting (in the frontal plane, around the sagittal axis) and axial rotation (in the transverse plane, around the vertical axis); and (2) the amount of rotation of the trunk compared with the position of the trunk at mid swing, including antero-posterior flexion (in the sagittal plane, around the transverse axis), lateral flexion (in the frontal plane, around the sagittal axis) and axial rotation (in the transverse plane, around the vertical axis). The outcomes for translation were computed for the pelvis and the trunk: antero-posterior translation (along the sagittal axis), lateral translation (along the transverse axis) and vertical translation (along the vertical axis). Statistics Statistics were performed using SPSS v20 (IBM, Chicago, IL). Descriptive statistics were calculated for baseline patient characteristics. Mean, standard deviation and range for continuous variables, and frequencies for categorical variables were calculated. A repeated measures analysis of variance with Bonferroni correction for multiple comparisons was used to analyze all outcome variables with the level of suspension as the withinsubject factor. The significance level (a) was set at 5%. Protocol All sensors of the electromagnetic tracker device were placed in a standardised manner when the participant was standing on the treadmill (Figure 1). During the whole protocol, the walking speed was 2 kmph and measurements (30 s) took place after a four-minute acclimatisation period [18]. First, the participants walked on the treadmill without robot assistance. Then, the Lokomat was fixated and the Litegait BWS system was fixed on the suspension fork. Trained health-care therapists, experienced with Lokomat gait training, installed the subjects. The suspension with the BWS system was 0%, 30% and 50% of the body weight

Trunk kinematics during robot-assisted gait

DOI: 10.3109/17483107.2014.888487

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Rotations of the trunk. In RATW, a significantly smaller anteroposterior flexion of the trunk during 50% (p ¼ 0.008) BWS and a significantly smaller axial rotation during 30% (p ¼ 0.036) and 50% (p ¼ 0.004) BWS compared with TW were found. A larger lateral flexion was found during RATW with 0% (p ¼ 0.012) BWS compared to with TW.

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Movements of the pelvis Translations of the pelvis. A significantly smaller anteroposterior translation was found with RATW with 0% (p  0.001), 30% (p  0.001) and 50% (p  0.001) BWS compared with TW (Figure 3). Furthermore, a significantly smaller lateral translation was found with RATW with 0% (p ¼ 0.013) and 50% (p ¼ 0.001) BWS compared with TW. No significant differences in vertical translation were found when RATW was compared with TW. Rotations of the pelvis. Significantly greater anteroposterior tilting was found during RATW with 0% (p  0.001), 30% (p  0.001) and 50% (p ¼ 0.006) BWS compared with TW. No statistically significant differences were found for lateral tilting or axial rotation when RATW was compared with TW. Comparison of RATW with different levels of BWS There was a significantly smaller lateral flexion (24.9%; p ¼ 0.045) and axial rotation (23.3%; p ¼ 0.003) of the trunk during RATW with 50% BWS compared with 0% BWS. There was also a significantly smaller axial rotation of the trunk (21.2%; p ¼ 0.005) during RATW with 50% BWS compared with 30% BWS.

Figure 1. Setup of the study. Table 1. Characteristics of participants.

Discussion Characteristics of participants

Body mass (kg)

Body height (m)

BMI (kg/m2)

Age (years)

Mean Standard deviation Range

63.4 8.26 53.0–80.0

1.72 0.08 160–190

21.4 1.51 19.2–24.7

27 3.81 21–33

of each participant. The order of walking conditions was randomised by drawing lots.

Results Participants In total, 18 persons (3 males and 15 females) participated in the study. Table 1 lists the characteristics of the participants. Most of the participants had limited preliminary experience with RATW with the Lokomat-system (one or two times). Table 2 shows the absolute values and their standard deviation of the maximal movement amplitudes during RATW with 0%, 30% and 50% BWS and during TW. RATW with 0%, 30% and 50% BWS compared with TW Movements of the trunk Translations of the trunk. The antero-posterior translation was significantly smaller during RATW with 0% (p  0.001), 30% (p  0.001) and 50% (p  0.001) BWS compared with TW (Figure 2). Futhermore, a significantly smaller lateral translation was found during RATW with 0% (p  0.001) and 50% (p  0.001) BWS compared with TW. No significant differences were found for the translations in the vertical direction between RATW and TW.

The aim of this study was to investigate the 3D kinematics of the trunk and the pelvis in healthy subjects during RATW with different levels of BWS (0%, 30% and 50%). The focus was to identify differences in maximum movement amplitudes comparing walking with robot assistance with different levels of BWS and walking without robot assistance. Trunk and pelvis movements Only a few studies have described trunk movements during TW with BWS. Pinte`r et al. (2006) studied the differential effect of 15–45% BWS on thorax and pelvis rotations, and Aaslund et al. (2008) studied the differences in thorax movements between 30% and 0% BWS. They found that a high percentage of BWS limited the inter-segmental coordination of the pelvis and thorax [19,20] and restricted the accelerations of the body segments in all directions [20]. In this study, compared with TW without robot assistance, during RATW with the use of BWS, diminutions of the translations of the trunk and the pelvis were found in the anteroposterior and lateral directions. Furthermore, a restriction in antero-posterior flexion and axial rotation of the trunk was found. These limitations in movements confirm the hypothesis of this study that the use of an exoskeleton robot device in combination with BWS leads to a restriction in the amplitudes of the movements of the thorax and pelvis. On the other hand, significant increases were found in lateral flexion of the trunk and antero-posterior tilting of the pelvis with RATW with the use of BWS compared with TW. These increases were more pronounced during walking with low levels of BWS and may be caused by the guidance force generated around the hips. During walking with a high level of BWS, the lateral flexion of the trunk might have been restricted by the suspension.

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Table 2. Movements of trunk and pelvis. RA + BWS: 0%

RA + BWS: 30%

RA + BWS: 50%

TW without RA

Mean SD Mean SD Mean SD

1.43 0.49 1.15 0.71 3.38 2.05

1.43 0.77 1.57 1.62 5.00 7.34

1.30 0.71 0.89 0.24 2.89 1.40

3.32 0.88 2.55 0.58 3.53 1.55

Mean SD Mean SD Mean SD

4.06 1.27 5.26 1.48 6.22 1.23

3.92 1.01 4.55 1.14 5.85 1.50

3.54 0.81 3.87 1.51 4.94 1.41

4.88 1.30 3.83 1.47 9.36 3.54

Mean SD Mean SD Mean SD

1.18 0.44 1.65 1.05 2.89 0.97

1.24 0.66 1.79 1.27 4.47 5.67

1.05 0.44 1.25 0.63 2.90 2.14

4.27 0.88 2.97 0.69 4.10 1.56

Mean SD Mean SD Mean SD

68.95 27.18 9.87 4.85 55.63 23.63

74.46 29.97 16.56 23.09 54.88 21.51

64.83 25.83 8.10 3.56 54.19 23.97

35.69 12.87 11.30 3.42 51.77 16.17

Movements of trunk and pelvis Translations of the thorax (cm) Anteroposterior translation Lateral translation Vertical translation Rotations of the thorax ( ) Anteroposterior flexion Lateral flexion Disabil Rehabil Assist Technol Downloaded from informahealthcare.com by UMEA University Library on 10/07/14 For personal use only.

Axial rotation Translations of the pelvis (cm) Anteroposterior translation Lateral translation Vertical translation Rotations of the pelvis ( ) Anteroposterior tilting Lateral tilting Axial rotation

Figure 2. Movements of the trunk during RATW with different levels of BWS. Presented as % difference compared with TW. TW: treadmill walking, BWS: body weight support, RATW: robot-assisted treadmill walking, A-P: antero-posterior, ,: significant difference (p  0.05).

Figure 3. Movements of the pelvis during RATW with different levels of BWS. Presented as % difference compared with TW. TW: treadmill walking, BWS: body weight support, RATW: robot-assisted treadmill walking, A-P: antero-posterior, ,: significant difference (p  0.05).

Aaslund et al. (2008) studied the effect of wearing a harness during TW [20]. They found that a tight harness restricts linear and rotational movements of the trunk and reduces shock absorption by the trunk. More shock is absorbed by the legs to avoid excessive cranial shock. In this study, the participants wore a harness during the entire protocol. A limitation of this study is that participants performed no trial of TW without the harness, this because of practical reasons related to the application of the sensors and electrodes. It is not clear if an increase in the level of BWS leads to more important changes in movement amplitudes. In this study, only for lateral flexion and axial rotation of the trunk was a significant

change in movement amplitude found for RATW, between the 50% BWS and the 0% BWS conditions. Between none of the BWS conditions during RATW were significant differences found in translations of the trunk and the pelvis and rotations of the pelvis. These data suggest that the changes in maximum movement amplitude were primarily due to the application and/or guidance force of the robotic device and the use of the harness of the suspension system more than due to the level of suspension itself. Pennycott et al. (2012) described that balance training during walking was not realistic with many of the current devices because of the aforementioned limited degrees of freedom and additional use of the BWS systems [4]. They reported that

Trunk kinematics during robot-assisted gait

DOI: 10.3109/17483107.2014.888487

the main components of balance, e.g. weight shifting from one leg to the other, were not permitted when using a robotic device and consequently, patients needed to actively exercise stabilisation by themselves [4]. This corroborates with the hypothesis of this study. Within general restrictions, the changes in movement amplitudes of the trunk and pelvis measured during RATW with the use of BWS could possibly lead to insufficient training of body balance during walking.

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Methodological considerations Mehrholz & Pohl (2012) found higher rates of independent walking with end-effector devices compared with exoskeletonbased training [21]. An example of an end-effector device is the Gait trainer [22]. Examples of exoskeleton devices are the Lokomat [2] and the Autoambulator [23]. The robotic device used in this study was the Lokomat system, and as a consequence, the data obtained in this study cannot be generalised to other robotic systems. The same considerations can be made about the use of the BWS system. Different types of suspension systems are available [24]. The system used in this study is the Levi system, a dynamic, low inertia suspension system that ensures a continuously adjustable BWS [25]. In motion analysis during overground walking, trial-to-trial variability and test-retest reliability can be a problem. Many repeated overground trials are required to obtain a sufficient number of representative strides [26]. Compared with overground walking, the gait on a treadmill results in a reduction in lateral tilting and axial rotation of the pelvis and lateral flexion of the trunk [27,28] and an increase in lumbar anterior flexion [16,20]. These differences a were very small and Riley et al. (2007) concluded that the gait analysis on a treadmill was therefore, functionally equivalent to measurements over ground [27]. The kinematics of the trunk and pelvis change when walking more slowly than normal [16,29–37]. The speed of the treadmill was set at 2 kmph during the whole protocol, due to the limitation in speed when walking with the robotic device. Walking at this velocity on the treadmill without robot assistance and BWS, healthy participants experienced it as very slow. Following the recommendation of Taylor et al. (1996), a four-minute adaptation period preceded every measurement to acclimatise the subjects to the walking speed [18]. Based on published studies, optoelectronic motion capturing is the more popular measurement technique than the electromagnetic motion tracking as used in this study. Even so, electromagnetic tracking has some advantages over image-based systems. It is not sensitive to low light and is relatively inexpensive; furthermore, intra-trial repeatability (coefficient of multiple determination ¼ 0.942) of the data was similar or even higher than the kinematic data in gait studies using video-based systems [38]. Skin to bone displacements could cause erroneous marker movements with respect to the underlying bone [39]. To avoid these soft tissue artifacts as much as possible, the sensors were placed on bony landmarks. Different definitions of the local frame of the trunk are possible: for example, a thorax definition in terms of the acromiae and sacrum [16] or, as in this study, a thorax frame based on a proximal point on the spine, the sternum and the sacrum [28]. The latter is more robust for it is not influenced by scapulothoracic motions induced by the arm swing during gait [40].

Implementations and conclusions There are significant differences in trunk and pelvis kinematics in healthy persons with RATW compared with TW. The results of this study demonstrate that during RATW with the use of BWS,

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there are (1) significantly smaller antero-posterior and lateral translations of the trunk and the pelvis; (2) significantly smaller antero-posterior flexion and axial rotation of the trunk; (3) significantly larger lateral flexion of the trunk; and (4) significantly greater antero-posterior tilting of the pelvis. When comparing RATW with different levels of BWS, the data suggest that the change in maximum amplitude of movement is due to the robotic device and the harness of the suspension system more than due to the level of suspension itself. The results of this study contribute to our knowledge of the influence of robot-assistance with BWS on the gait patterns, which could improve gait rehabilitation with the use of robotic devices. Additional research is recommended to further assess the influence of robot assistance on human gait.

Acknowledgements We are grateful to the VUB language centre (ITO) for proofreading the text in English. We would also like to thank the therapists of the rehabilitation centre for participation and assistance in the study.

Test location and ethical commission All measurements were performed at the Rehabilitation Centre St. Ursula, Jessa Hospital, Herk-de-Stad, Belgium. The protocol was approved by the local ethics commission of the university (BUN B1432008499) and the rehabilitation centre (12.11/ fys12.02).

Declaration of interest We confirm that there are no conflicts of interest associated with this publication and there has been no financial support for this work that could have influenced its outcome. All authors were fully involved in the study and preparation of the manuscript and the results of this study has not been and will not be submitted for publication elsewhere.

References 1. Hesse S, Schmidt H, Werner C, Bardeleben A. Upper and lower extremity robotic devices for rehabilitation and for studying motor control. Curr Opin Neurol 2003;16:705–10. 2. Jezernik S, Colombo G, Keller T, et al. Robotic orthosis lokomat: a rehabilitation and research tool. Neuromodulation 2003;6:108–15. 3. Visintin M, Barbeau H, Korner-Bitensky N, Mayo NE. A new approach to retrain gait in stroke patients through body weight support and treadmill stimulation. Stroke 1998;29:1122–8. 4. Pennycott A, Wyss D, Vallery H, et al. Towards more effective robotic gait training for stroke rehabilitation: a review. J Neuroeng Rehabil 2012;9:65. doi: 10.1186/1743-0003-9-65. 5. Mehrholz J, Kugler J, Pohl M. Locomotor training for walking after spinal cord injury. Cochrane Database Syst Rev 2008;(2): CD006676. 6. Swinnen E, Beckwee D, Pinte D, et al. Treadmill training in multiple sclerosis: can body weight support or robot assistance provide added value? A systematic review. Mult Scler Int 2012;2012:240274. http://dx.doi.org/10.1155/2012/240274. 7. Swinnen E, Duerinck S, Baeyens JP, et al. Effectiveness of robotassisted gait training in persons with spinal cord injury: a systematic review. J Rehabil Med 2010;42:520–6. 8. Mehrholz J, Friis R, Kugler J, et al. Treadmill training for patients with Parkinson’s disease. Cochrane Database Syst Rev 2010;(1): CD007830. 9. Lewek MD. The influence of body weight support on ankle mechanics during treadmill walking. J Biomech 2011;44:128–33. 10. Kyvelidou A, Kurz MJ, Ehlers JL, Stergiou N. Aging and partial body weight support affects gait variability. J Neuroeng Rehabil 2008;5:22. doi: 10.1186/1743-0003-5-22.

Disabil Rehabil Assist Technol Downloaded from informahealthcare.com by UMEA University Library on 10/07/14 For personal use only.

6

E. Swinnen et al.

11. Hidler J, Wisman W, Neckel N. Kinematic trajectories while walking within the Lokomat robotic gait-orthosis. Clin Biomech 2008;23:1251–9. 12. Neckel N, Wisman W, Hidler J. Limb alignment and kinematics inside a Lokomat robotic orthosis. Conf Proc IEEE Eng Med Biol Soc 2006;1:2698–701. 13. Neckel ND, Blonien N, Nichols D, Hidler J. Abnormal joint torque patterns exhibited by chronic stroke subjects while walking with a prescribed physiological gait pattern. J Neuroeng Rehabil 2008;5:19. doi: 10.1186/1743-0003-5-19. 14. Thorstensson A, Nilsson J, Carlson H, Zomlefer MR. Trunk movements in human locomotion. Acta Physiologica Scandinavica 1984;121:9–22. 15. Saunders JB, Inman VT, Eberhart HD. The major determinants in normal and pathological gait. J Bone Joint Surg Am 1953;35-A: 543–58. 16. Nymark JR, Balmer SJ, Melis EH, et al. Electromyographic and kinematic nondisabled gait differences at extremely slow overground and treadmill walking speeds. J Rehabil Res Dev 2005;42:523–34. 17. Krewer C, Muller F, Husemann B, et al. The influence of different Lokomat walking conditions on the energy expenditure of hemiparetic patients and healthy subjects. Gait Posture 2007;26:372–7. 18. Taylor NF, Evans OM, Goldie PA. Angular movements of the lumbar spine and pelvis can be reliably measured after 4 minutes of treadmill walking. Clin Biomech 1996;11:484–6. 19. Pinte`r I, Vreugdenhil A, Janssens T, Lamoth C. Effect of body weight support and walking speed on inter-segmental coordination during gait. Gait Posture 2006;24:S207–8. 20. Aaslund MK, Moe-Nilssen R. Treadmill walking with body weight support effect of treadmill, harness and body weight support systems. Gait Posture 2008;28:303–8. 21. Mehrholz J, Pohl M. Electromechanical-assisted gait training after stroke: a systematic review comparing end-effector and exoskeleton devices. J Rehab Med 2012;44:193–9. 22. Hesse S, Uhlenbrock D. A mechanized gait trainer for restoration of gait. J Rehabil Res Dev 2000;37:701–8. 23. Schmidt H, Werner C, Bernhardt R, et al. Gait rehabilitation machines based on programmable footplates. J Neuroeng Rehabil 2007;4:2. doi: 10.1186/1743-0003-4-2. 24. Finch L, Barbeau H, Arsenault B. Influence of body weight support on normal human gait: development of a gait retraining strategy. Phys Ther 1991;71:842–55; discussion 855–6.

Disabil Rehabil Assist Technol, Early Online: 1–6

25. Hocoma. 2013. Available from: http://www.hocoma.com/products/ lokomat/lokomatpro/features-functions/#bodyweight [last accessed Sep 2013]. 26. White SC, Yack HJ, Tucker CA, Lin HY. Comparison of vertical ground reaction forces during overground and treadmill walking. Med Sci Sports Exerc 1998;30:1537–42. 27. Riley PO, Paolini G, Della Croce U, et al. A kinematic and kinetic comparison of overground and treadmill walking in healthy subjects. Gait Posture 2007;26:17–24. 28. Vogt L, Pfeifer K, Banzer W. Comparison of angular lumbar spine and pelvis kinematics during treadmill and overground locomotion. Clin Biomech (Bristol, Avon) 2002;17:162–5. 29. Crosbie J, Vachalathiti R, Smith R. Patterns of spinal motion during walking. Gait Posture 1997;5:6–12. 30. Crosbie J, Vachalathiti R, Smith R. Age, gender and speed effects on spinal kinematics during walking. Gait Posture 1997;5:13–20. 31. Saunders SW, Schache A, Rath D, Hodges PW. Changes in three dimensional lumbo-pelvic kinematics and trunk muscle activity with speed and mode of locomotion. Clin Biomech (Bristol, Avon) 2005; 20:784–93. 32. Taylor NF, Goldie PA, Evans OM. Angular movements of the pelvis and lumbar spine during self-selected and slow walking speeds. Gait Posture 1999;9:88–94. 33. Wagenaar RC, Beek WJ. Hemiplegic gait: a kinematic analysis using walking speed as a basis. J Biomech 1992;25:1007–15. 34. Stokes VP, Andersson C, Forssberg H. Rotational and translational movement features of the pelvis and thorax during adult human locomotion. J Biomech 1989;22:43–50. 35. Feipel V, De Mesmaeker T, Klein P, Rooze M. Three-dimensional kinematics of the lumbar spine during treadmill walking at different speeds. Eur Spine J 2001;10:16–22. 36. Chapman W, Kurokawa M. Some observations on the transverse rotations of the human trunk during locomotion. Bull Prosthet Res 1969;Spring:38–59. 37. van Emmerik RE, Wagenaar RC. Effects of walking velocity on relative phase dynamics in the trunk in human walking. J Biomech 1996;29:1175–84. 38. Mills PM, Morrison S, Lloyd DG, Barrett RS. Repeatability of 3D gait kinematics obtained from an electromagnetic tracking system during treadmill locomotion. J Biomech 2007;40:1504–11. 39. Leardini A, Chiari L, Della Croce U, Cappozzo A. Human movement analysis using stereophotogrammetry. Part 3. Soft tissue artifact assessment and compensation. Gait Posture 2005;21:212–25. 40. Inman VT. Human locomotion. Can Med Assoc J 1996;94:1047–54.

Walking with robot assistance: the influence of body weight support on the trunk and pelvis kinematics.

The goal was to assess in healthy participants the three-dimensional kinematics of the pelvis and the trunk during robot-assisted treadmill walking (R...
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