Investigation on Inter-Limb Coordination and Motion Stability, Intensity and Complexity of Trunk and Limbs during Hands-Knees Crawling in Human Adults

This study aimed to investigate the inter-limb coordination pattern and the stability, intensity, and complexity of the trunk and limbs motions in human crawling under different speeds. Thirty healthy human adults finished hands-knees crawling trials on a treadmill at six different speeds (from 1 km/h to 2.5 km/h). A home-made multi-channel acquisition system consisting of five 3-axis accelerometers (ACC) and four force sensors was used for the data collection. Ipsilateral phase lag was used to represent inter-limb coordination pattern during crawling and power, harmonic ratio, and sample entropy of acceleration signals were adopted to depict the motion intensity, stability, and complexity of trunk and limbs respectively. Our results revealed some relationships between inter-limb coordination patterns and the stability and complexity of trunk movement. Trot-like crawling pattern was found to be the most stable and regular one at low speed in the view of trunk movement, and no-limb-pairing pattern showed the lowest stability and the greatest complexity at high speed. These relationships could be used to explain why subjects tended to avoid no-limb-pairing pattern when speed was over 2 km/h no matter which coordination type they used at low speeds. This also provided the evidence that the central nervous system (CNS) chose a stable inter-limb coordination pattern to keep the body safe and avoid tumbling. Although considerable progress has been made in the study of four-limb locomotion, much less is known about the reasons for the variety of inter-limb coordination. The research results of the exploration on the inter-limb coordination pattern choice during crawling from the standpoint of the motion stability, intensity, and complexity of trunk and limbs sheds light on the underlying motor control strategy of the human CNS and has important significance in the fields of clinical diagnosis, rehabilitation engineering, and kinematics research.

[1]  Jessica L. Allen,et al.  Neuromechanical Principles Underlying Movement Modularity and Their Implications for Rehabilitation , 2015, Neuron.

[2]  B. Auvinet,et al.  Reference data for normal subjects obtained with an accelerometric device. , 2002, Gait & posture.

[3]  Nigel H. Lovell,et al.  Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring , 2006, IEEE Transactions on Information Technology in Biomedicine.

[4]  Daniel Schmitt,et al.  Insights into the evolution of human bipedalism from experimental studies of humans and other primates , 2003, Journal of Experimental Biology.

[5]  Sean Gallagher,et al.  Locomotion in restricted space: kinematic and electromyographic analysis of stoopwalking and crawling. , 2011, Gait & posture.

[6]  Jaynie F. Yang,et al.  Developmental constraints of quadrupedal coordination across crawling styles in human infants. , 2012, Journal of neurophysiology.

[7]  M. Redfern,et al.  A Comprehensive Assessment of Gait Accelerometry Signals in Time, Frequency and Time-Frequency Domains , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[8]  Jesse W Young,et al.  Is primate-like quadrupedalism necessary for fine-branch locomotion? A test using sugar gliders (Petaurus breviceps). , 2010, Journal of human evolution.

[9]  J. VanSwearingen,et al.  Harmonic ratios: a quantification of step to step symmetry. , 2013, Journal of biomechanics.

[10]  L. Chou,et al.  Effect of walking speed on inter-joint coordination differs between young and elderly adults. , 2012, Journal of biomechanics.

[11]  Jaynie F. Yang,et al.  Interlimb coordination in human crawling reveals similarities in development and neural control with quadrupeds. , 2009, Journal of neurophysiology.

[12]  H. Yack,et al.  Dynamic stability in the elderly: identifying a possible measure. , 1993, Journal of gerontology.

[13]  J. Richman,et al.  Physiological time-series analysis using approximate entropy and sample entropy. , 2000, American journal of physiology. Heart and circulatory physiology.

[14]  W. McIlroy,et al.  Population Differences in Postural Response Strategy Associated with Exposure to a Novel Continuous Perturbation Stimuli: Would Dancers Have Better Balance on a Boat? , 2016, PLoS ONE.

[15]  Stefano Piazza,et al.  A motor learning oriented, compliant and mobile Gait Orthosis , 2012 .

[16]  Herman Pontzer,et al.  Bipedal and quadrupedal locomotion in chimpanzees. , 2014, Journal of human evolution.

[17]  Daniel Schmitt,et al.  Understanding the adaptive value of diagonal-sequence gaits in primates: a comment on Shapiro and Raichlen, 2005. , 2007, American journal of physical anthropology.

[18]  Jesse W. Young,et al.  Human Quadrupeds, Primate Quadrupedalism, and Uner Tan Syndrome , 2014, PloS one.

[19]  Lisa M Muratori,et al.  Applying principles of motor learning and control to upper extremity rehabilitation. , 2013, Journal of hand therapy : official journal of the American Society of Hand Therapists.

[20]  F Lacquaniti,et al.  Features of hand-foot crawling behavior in human adults. , 2012, Journal of neurophysiology.

[21]  Mark L. Latash,et al.  The bliss (not the problem) of motor abundance (not redundancy) , 2012, Experimental Brain Research.

[22]  V. Dietz,et al.  Arm to leg coordination in humans during walking, creeping and swimming activities , 2001, Experimental Brain Research.

[23]  David P. Miller,et al.  Novel Assistive Device for Teaching Crawling Skills to Infants , 2015, FSR.

[24]  Lenoir H. Burnside,et al.  Coordination in the locomotion of infants , 1927 .

[25]  D. Owaki,et al.  Simple robot suggests physical interlimb communication is essential for quadruped walking , 2013, Journal of The Royal Society Interface.

[26]  T. McMahon,et al.  Scaling Stride Frequency and Gait to Animal Size: Mice to Horses , 1974, Science.

[27]  Roberto Sassi,et al.  Parametric estimation of sample entropy in heart rate variability analysis , 2014, Biomed. Signal Process. Control..

[28]  Hui Zhong,et al.  Kinematic and EMG determinants in quadrupedal locomotion of a non-human primate (Rhesus). , 2005, Journal of neurophysiology.

[29]  Jesse W. Young,et al.  Quadrupedal Locomotion of Saimiri boliviensis: A Comparison of Field and Laboratory-based Kinematic Data , 2011 .

[30]  J P Scholz,et al.  Dynamic pattern theory--some implications for therapeutics. , 1990, Physical therapy.

[31]  J. Young.  Gait selection and the ontogeny of quadrupedal walking in squirrel monkeys (Saimiri boliviensis). , 2012, American journal of physical anthropology.

[32]  M Hildebrand,et al.  Symmetrical gaits of horses. , 1965, Science.

[33]  J Whitall,et al.  Individual Differences and Similarities in the Stability, Timing Consistency, and Natural Frequency of Rhythmic Coordinated Actions , 2001, Research quarterly for exercise and sport.

[34]  D. Raichlen,et al.  Lateral sequence walking in infant Papio cynocephalus: implications for the evolution of diagonal sequence walking in primates. , 2005, American journal of physical anthropology.

[35]  W. A. Sparrow,et al.  The coordination and control of human creeping with increases in speed , 1994, Behavioural Brain Research.

[36]  J. Hamill,et al.  Energetic Cost and Stability during Human Walking at the Preferred Stride Frequency , 1995 .

[37]  D. F. Hoyt,et al.  Gait and the energetics of locomotion in horses , 1981, Nature.

[38]  Cassie Wilson,et al.  Intra-limb coordinative adaptations in cycling , 2012, Sports biomechanics.