Arm and leg coordination during treadmill walking in individuals with motor incomplete spinal cord injury: A preliminary study

Tester, Nicole J.; Barbeau, Hugues; Howland, Dena R.; Cantrell, Amy; Behrman, Andrea L.

doi:10.1016/j.gaitpost.2012.01.004

Cited by 28 publications

(20 citation statements)

References 30 publications

(41 reference statements)

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“…In addition, given the fact that analyzing arm-swing patterns in terms of their amplitude and coordination with lower limbs (interlimb coordination) have become increasingly important in rehabilitation of patients with different walking disabilities [12,50,16], the plots in Fig. 4 may serve as guidelines for diagnosis and assessment of a patients' arm swing.…”

Section: Discussionmentioning

confidence: 99%

“…The effect of arm-swing integration in gait rehabilitation becomes more pronounced when patients practice correct arm-swing patterns [8]. However, such patients may have impaired or abnormal arm-swing patterns [5,12,13,14,15,16,17,18], and may require assistance to attain a more natural arm-swing pattern. Thus, the integration of arm swing in gait rehabilitation may lead to more effective walking recovery for patients with walking impairments [6,8,12,19].…”

Section: Introductionmentioning

confidence: 99%

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Comprehensive quantitative investigation of arm swing during walking at various speed and surface slope conditions

Hejrati

Chesebrough

Foreman

et al. 2016

Human Movement Science

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Previous studies have shown that inclusion of arm swing in gait rehabilitation leads to more effective walking recovery in patients with walking impairments. However, little is known about the correct arm-swing trajectories to be used in gait rehabilitation given the fact that changes in walking conditions affect arm-swing patterns. In this paper we present a comprehensive look at the effects of a variety of conditions on arm-swing patterns during walking. The results describe the effects of surface slope, walking speed, and physical characteristics on arm-swing patterns in healthy individuals. We propose data-driven mathematical models to describe arm-swing trajectories. Thirty individuals (fifteen females and fifteen males) with a wide range of height (1.58-1.91m) and body mass (49-98kg), participated in our study. Based on their self-selected walking speed, each participant performed walking trials with four speeds on five surface slopes while their whole-body kinematics were recorded. Statistical analysis showed that walking speed, surface slope, and height were the major factors influencing arm swing during locomotion. The results demonstrate that data-driven models can successfully describe arm-swing trajectories for normal gait under varying walking conditions. The findings also provide insight into the behavior of the elbow during walking.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comprehensive quantitative investigation of arm swing during walking at various speed and surface slope conditions

Hejrati

Chesebrough

Foreman

et al. 2016

Human Movement Science

View full text Add to dashboard Cite

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“…During walking or running, in healthy adults the characteristic movement patterns between the upper and lower limbs are related to each other [25]. To create and study angle-angle diagrams, we use a model of the human body created in MatLab software [26,21].…”

Section: Cyclograms and Prediction Of Joint Anglesmentioning

confidence: 99%

Analysis and prediction of upper extremity movements by cyclograms

2014

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AbstractQuantification of upper extremity movement is a common objective in both research and clinical practice. Currently, methods based on angle-angle diagrams, also called cyclograms, seem to be promising. Nevertheless, compared to the study of lower limbs, the concept of angle-angle diagrams has not been systematically used to study upper limb movements during walking. The paper describes two examples of new methods based on angle-angle diagrams for application in rehabilitation and assistive robotics. The cyclograms represent information about the relationship between the angles and their changes over time. We used cyclograms as patterns for learning artificial neural networks and predicting the movement of upper-limb. Together with artificial intelligence, cyclograms offer wide scope of application in prosthesis control systems. Using bilateral cyclogram, the information about the relationship between the right and left arm joint angles is used to evaluate the symmetry of movements. The method based on the orientation of the bilateral cyclogram can be used as an additional method for determining the symmetry of movements of the upper limbs or exo-prosthesis.

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“…Normalization of the data has been described in detail by Perry [27]. During walking or running, the characteristic movement patterns of the joint of upper and lower limbs are related to each other in healthy adults [28]. Using the diagrams of average joint angles during walking ( Fig.3 and Fig.4.…”

Section: Fuzzy Rule Based Expert System For Identifying Upper Extrmentioning

confidence: 99%

The estimation of the joint angles of upper limb during walking using fuzzy logic system and relation maps

Skoda

Kutílek

Socha

et al. 2015

2015 IEEE 13th International Symposium on Applied Machine Intelligence and Informatics (SAMI)

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The objects of the study including determining the relationships between movements of upper extremities identifying joint angles using a fuzzy logic system (FS). The authors analyzed ranges of joint angles and simple rhythmical movement: swinging segments of walking subjects´ arms moving in-phase (synchronously) or antiphase (reciprocally), and designed fuzzy expert system which has never been described before. The set of data to create and study fuzzy logic for identifying upper extremity angles was measured in ten volunteers. An Xbus Kit system was used to measure upper limb movements. The joint angles in the sagittal plane and angle in the frontal plane were determined and relation maps of the in-phase and antiphase movements in the contralateral and ipsilateral joints were designed. The if-then rules were derived from experimental findings and knowledge about ranges of angles and relations between angles of upper limbs during walking. The estimated values of joint angles were compared with the observed values of joint angles. Spearman's correlation coefficients were calculated for this purpose, and strong correlations for the walking speed of 3 km/h and 5 km/h were observed. The FS based on relation maps of the inphase and anti-phase movements in the contralateral and ipsilateral joints have shown to be suitable for the estimation of joint angles of upper limb during walking. The concept of the FS offers a wide range of application in rehabilitation and prostheses design.

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Arm and leg coordination during treadmill walking in individuals with motor incomplete spinal cord injury: A preliminary study

Cited by 28 publications

References 30 publications

Comprehensive quantitative investigation of arm swing during walking at various speed and surface slope conditions

Comprehensive quantitative investigation of arm swing during walking at various speed and surface slope conditions

Analysis and prediction of upper extremity movements by cyclograms

The estimation of the joint angles of upper limb during walking using fuzzy logic system and relation maps

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