scholarly journals Vertical displacement of the centre of mass during walking in people with diabetes and diabetic neuropathy does not explain their higher metabolic cost of walking

2019 ◽  
Vol 83 ◽  
pp. 85-90 ◽  
Author(s):  
M. Petrovic ◽  
C.N. Maganaris ◽  
F.L. Bowling ◽  
A.J.M. Boulton ◽  
N.D. Reeves
Keyword(s):  
Diabetic Neuropathy ◽  
Metabolic Cost ◽  
Vertical Displacement ◽  
Centre Of Mass

scholarly journals Medial-lateral centre of mass displacement and base of support are equally good predictors of metabolic cost in amputee walking

2017 ◽  
Vol 51 ◽  
pp. 41-46 ◽  
Author(s):  
R.A. Weinert-Aplin ◽  
M. Twiste ◽  
H.L. Jarvis ◽  
A.N. Bennett ◽  
R.J. Baker
Keyword(s):  
Metabolic Cost ◽  
Centre Of Mass ◽  
Mass Displacement ◽  
Base Of Support

Optimum gradient of mountain paths

1995 ◽  
Vol 79 (5) ◽  
pp. 1698-1703 ◽  
Author(s):  
A. E. Minetti
Keyword(s):  
Energy Expenditure ◽  
High Altitude ◽  
Body Mass ◽  
Metabolic Cost ◽  
Vertical Displacement ◽  
Transmission Efficiency ◽  
Metabolic Power ◽  
Gait Biomechanics ◽  
Overall Efficiency ◽  
Downhill Walking

By combining the experiment results of R. Margaria (Atti Accad. Naz. Lincei Memorie 7: 299–368, 1938), regarding the metabolic cost of gradient locomotion, together with recent insights on gait biomechanics, a prediction about the most economical gradient of mountain paths (approximately 25%) is obtained and interpreted. The pendulum-like mechanism of walking produces a waste of mechanical work against gravity within the gradient range of up to 15% (the overall efficiency is dominated by the low transmission efficiency), whereas for steeper values only the muscular efficiency is responsible for the (slight) metabolic change (per meter of vertical displacement) with respect to gradient. The speeds at the optimum gradient turned out to be approximately 0.65 m/s (+0.16 m/s vertical) and 1.50 m/s (-0.36 m/s vertical), for uphill and downhill walking, respectively, and the ascensional energy expenditure was 0.4 and 2.0 ml O2.kg body mass-1.vertical m-1 climbed or descended. When the metabolic power becomes a burden, as in high-altitude mountaineering, the optimum gradient should be reduced. A sample of real mountain path gradients, experimentally measured, mimics the obtained predictions.

scholarly journals A method for tracking centre of mass displacement during non-seated cycling using an inertial sensor

2020 ◽  
Author(s):  
Ross D. Wilkinson ◽  
Glen A. Lichtwark
Keyword(s):  
Repeated Measures ◽  
Inertial Sensor ◽  
Mechanical Energy ◽  
Vertical Displacement ◽  
Cycling Performance ◽  
Measurement Unit ◽  
Centre Of Mass ◽  
Joint Power ◽  
Lower Back ◽  
Marker Cluster

Abstract Instantaneous crank power does not equal total joint power if a rider's centre of mass (CoM) gains and loses mechanical energy. Thus, estimating CoM motion and the associated energy changes can provide valuable information about cycling performance. To date, an accurate and precise method for tracking CoM motion during outdoor cycling has not been validated. Purpose: To assess the suitability of an inertial measurement unit (IMU) for tracking CoM motion during non-seated cycling by comparing vertical displacement derived from an inertial sensor mounted to the lower back of the rider to an attached marker cluster and to a kinematic estimate of vertical CoM displacement from a full-body musculoskeletal model (Model). Methods: IMU and motion capture data were collected synchronously for 10 seconds while participants (n = 7) cycled on an ergometer in a non-seated posture at three power outputs and two cadences. A limits of agreement analysis, corrected for repeated measures, was performed on the range of vertical displacement between the IMU and the two other measures. A total of 303 crank cycles were analysed. Results: The IMU measured vertical displacement of the marker cluster with high accuracy (1.6 mm) and precision (3.5 mm) but substantially overestimated the kinematic estimate of rider CoM displacement. Conclusion: We interpret these findings as evidence that a single IMU placed on the lower back is unsuitable for tracking rider CoM displacement during non-seated cycling if the linearly increasing overestimation is unaccounted for.

scholarly journals Does an inverted pendulum model represent the gait of individuals with unilateral transfemoral amputation while walking over level ground?

2018 ◽  
Vol 43 (2) ◽  
pp. 221-226 ◽  
Author(s):  
Gerda Strutzenberger ◽  
Nathalie Alexander ◽  
Alan De Asha ◽  
Hermann Schwameder ◽  
Cleveland Thomas Barnett
Keyword(s):  
Gait Cycle ◽  
Inverted Pendulum ◽  
Metabolic Cost ◽  
Centre Of Mass ◽  
Transfemoral Amputation ◽  
Prosthetic Device ◽  
Relative Time ◽  
Prosthetic Limb ◽  
Inverted Pendulum Model ◽  
Pendulum Model

Background: An inverted pendulum model represents the mechanical function of able-bodied individuals walking accurately, with centre of mass height and forward velocity data plotting as sinusoidal curves, 180° out of phase. Objectives: This study investigated whether the inverted pendulum model represented level gait in individuals with a unilateral transfemoral amputation. Study Design: Controlled trial. Methods: Kinematic and kinetic data from 10 individuals with unilateral transfemoral amputation and 15 able-bodied participants were recorded during level walking. Results: During level walking, the inverted pendulum model described able-bodied gait well throughout the gait cycle, with median relative time shifts between centre of mass height and velocity maxima and minima between 1.2% and 1.8% of gait cycle. In the group with unilateral transfemoral amputation, the relative time shift was significantly increased during the prosthetic-limb initial double-limb support phase by 6.3%. Conclusion: The gait of individuals with unilateral transfemoral amputation shows deviation from a synchronous inverted pendulum model during prosthetic-limb stance. The reported divergence may help explain such individuals’ increased metabolic cost of gait. Temporal divergence of inverted pendulum behaviour could potentially be utilised as a tool to assess the efficacy of prosthetic device prescription. Clinical relevance The size of the relative time shifts between centre of mass height and velocity maxima and minima could potentially be used as a tool to quantify the efficacy of innovative prosthetic device design features aimed at reducing the metabolic cost of walking and improving gait efficiency in individuals with amputation.

Altered centre of mass vertical displacement in Parkinson disease patients during walking

2015 ◽  
Vol 42 ◽  
pp. S13
Author(s):  
Mariangela Dipaola ◽  
Esteban Pavan ◽  
Ioannis U. Isaias ◽  
Carlo A. Frigo
Keyword(s):  
Parkinson Disease ◽  
Vertical Displacement ◽  
Centre Of Mass

scholarly journals A novel Movement Amplification environment reveals effects of controlling lateral centre of mass motion on gait stability and metabolic cost

2020 ◽  
Vol 7 (1) ◽  
pp. 190889
Author(s):  
Mengnan/Mary Wu ◽  
Geoffrey L. Brown ◽  
Jane L. Woodward ◽  
Sjoerd M. Bruijn ◽  
Keith E. Gordon
Keyword(s):  
Metabolic Cost ◽  
Mass Motion ◽  
Step Width ◽  
Centre Of Mass ◽  
Cost Of Transport ◽  
Gait Patterns ◽  
Gait Stability ◽  
Foot Placement ◽  
Base Of Support ◽  
Healthy Participants

During human walking, the centre of mass (COM) laterally oscillates, regularly transitioning its position above the two alternating support limbs. To maintain upright forward-directed walking, lateral COM excursion should remain within the base of support, on average. As necessary, humans can modify COM motion through various methods, including foot placement. How the nervous system controls these oscillations and the costs associated with control are not fully understood. To examine how lateral COM motions are controlled, healthy participants walked in a ‘Movement Amplification’ force field that increased lateral COM momentum in a manner dependent on the participant's own motion (forces were applied to the pelvis proportional to and in the same direction as lateral COM velocity). We hypothesized that metabolic cost to control lateral COM motion would increase with the gain of the field. In the Movement Amplification field, participants were significantly less stable than during baseline walking. Stability significantly decreased as the field gain increased. Participants also modified gait patterns, including increasing step width, which increased the metabolic cost of transport as the field gain increased. These results support previous research suggesting that humans modulate foot placement to control lateral COM motion, incurring a metabolic cost.

scholarly journals A method for tracking centre of mass displacement during non-seated cycling using an inertial sensor

2020 ◽  
Author(s):  
Ross D. Wilkinson ◽  
Glen A. Lichtwark
Keyword(s):  
Repeated Measures ◽  
Inertial Sensor ◽  
Mechanical Energy ◽  
Vertical Displacement ◽  
Cycling Performance ◽  
Measurement Unit ◽  
Centre Of Mass ◽  
Joint Power ◽  
Lower Back ◽  
Marker Cluster

Instantaneous crank power does not equal total joint power if a rider's centre of mass (CoM) gains and loses mechanical energy. Thus, estimating CoM motion and the associated energy changes can provide valuable information about cycling performance. To date, an accurate and precise method for tracking CoM motion during outdoor cycling has not been validated. \textbf{Purpose:} To assess the suitability of an inertial measurement unit (IMU) for tracking CoM motion during non-seated cycling by comparing vertical displacement derived from an inertial sensor mounted to the lower back of the rider to an attached marker cluster and to a kinematic estimate of vertical CoM displacement from a full-body musculoskeletal model (Model). \textbf{Methods:} IMU and motion capture data were collected synchronously for 10 seconds while participants ($n=7$) cycled on an ergometer in a non-seated posture at three power outputs and two cadences. A limits of agreement analysis, corrected for repeated measures, was performed on the range of vertical displacement between the IMU and the two other measures. A total of 303 crank cycles were analysed. \textbf{Results:} The IMU measured vertical displacement of the marker cluster with high accuracy (1.6 mm) and precision (3.5 mm) but substantially overestimated the kinematic estimate of rider CoM displacement. \textbf{Conclusion:} We interpret these findings as evidence that a single IMU placed on the lower back is unsuitable for tracking rider CoM displacement during non-seated cycling if the linearly increasing overestimation is unaccounted for.

scholarly journals Mechanical determinants of the minimum energy cost of gradient running in humans.

1994 ◽  
Vol 195 (1) ◽  
pp. 211-225 ◽  
Author(s):  
A E Minetti ◽  
L P Ardigò ◽  
F Saibene
Keyword(s):  
Human Subjects ◽  
Minimum Energy ◽  
Metabolic Cost ◽  
The Body ◽  
Mechanical Work ◽  
Stride Frequency ◽  
Centre Of Mass ◽  
Negative Part ◽  
External Work ◽  
Level Running

The metabolic cost and the mechanical work of running at different speeds and gradients were measured on five human subjects. The mechanical work was partitioned into the internal work (Wint) due to the speed changes of body segments with respect to the body centre of mass and the external work (Wext) due to the position and speed changes of the body centre of mass in the environment. Wext was further divided into a positive part (W+ext) and a negative part (W-ext), associated with the energy increases and decreases, respectively, over the stride period. For all constant speeds, the most economical gradient was -10.6 +/-0.5% (S.D., N = 5) with a metabolic cost of 146.8 +/- 3.8 ml O2 kg-1 km-1. At each gradient, there was a unique W+ext/W-ext ratio (which was 1 in level running), irrespective of speed, with a tendency for W-ext and W+ext to disappear above a gradient of +30% and below a gradient of -30%, respectively. Wint was constant within each speed from a gradient of -15% to level running. This was the result of a nearly constant stride frequency at all negative gradients. The constancy of Wint within this gradient range implies that Wint has no role in determining the optimum gradient. The metabolic cost C was predicted from the mechanical experimental data according to the following equation: [formula: see text] where eff- (0.80), eff+ (0.18) and effi (0.30) are the efficiencies of W-ext, W+ext and Wint, respectively, and el- and el+ represent the amounts of stored and released elastic energy, which are assumed to be 55J step-1. The predicted C versus gradient curve coincides with the curve obtained from metabolic measurements. We conclude that W+ext/W-ext partitioning and the eff+/eff- ratio, i.e. the different efficiency of the muscles during acceleration and braking, explain the metabolic optimum gradient for running of about -10%.

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