Dataset Information

Magnetic Resonance-Compatible Arm-Crank Ergometry: A New Platform Linking Whole-Body Calorimetry to Upper-Extremity Biomechanics and Arm Muscle Metabolism.

ABSTRACT:

Introduction

Evaluation of the effect of human upper-body training regimens may benefit from knowledge of local energy expenditure in arm muscles. To that end, we developed a novel arm-crank ergometry platform for use in a clinical magnetic resonance (MR) scanner with ³¹P spectroscopy capability to study arm muscle energetics. Complementary datasets on heart-rate, whole-body oxygen consumption, proximal arm-muscle electrical activity and power output, were obtained in a mock-up scanner. The utility of the platform was tested by a preliminary study over 4 weeks of skill practice on the efficiency of execution of a dynamic arm-cranking task in healthy subjects.

Results

The new platform successfully recorded the first ever in vivo ³¹P MR spectra from the human biceps brachii (BB) muscle during dynamic exercise in five healthy subjects. Changes in BB energy- and pH balance varied considerably between individuals. Surface electromyography and mechanical force recordings revealed that individuals employed different arm muscle recruitment strategies, using either predominantly elbow flexor muscles (pull strategy; two subjects), elbow extensor muscles (push strategy; one subject) or a combination of both (two subjects). The magnitude of observed changes in BB energy- and pH balance during ACT execution correlated closely with each strategy. Skill practice improved muscle coordination but did not alter individual strategies. Mechanical efficiency on group level seemed to increase as a result of practice, but the outcomes generated by the new platform showed the additional caution necessary for the interpretation that total energy cost was actually reduced at the same workload.

Conclusion

The presented platform integrates dynamic in vivo ³¹P MRS recordings from proximal arm muscles with whole-body calorimetry, surface electromyography and biomechanical measurements. This new methodology enables evaluation of cyclic motor performance and outcomes of upper-body training regimens in healthy novices. It may be equally useful for investigations of exercise physiology in lower-limb impaired athletes and wheelchair users as well as frail patients including patients with debilitating muscle disease and the elderly.

SUBMITTER: Vegter RJK

PROVIDER: S-EPMC7933461 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Magnetic Resonance-Compatible Arm-Crank Ergometry: A New Platform Linking Whole-Body Calorimetry to Upper-Extremity Biomechanics and Arm Muscle Metabolism.

Vegter Riemer J K RJK van den Brink Sebastiaan S Mouton Leonora J LJ Sibeijn-Kuiper Anita A van der Woude Lucas H V LHV Jeneson Jeroen A L JAL

Frontiers in physiology 20210219

<h4>Introduction</h4>Evaluation of the effect of human upper-body training regimens may benefit from knowledge of local energy expenditure in arm muscles. To that end, we developed a novel arm-crank ergometry platform for use in a clinical magnetic resonance (MR) scanner with <sup>31</sup>P spectroscopy capability to study arm muscle energetics. Complementary datasets on heart-rate, whole-body oxygen consumption, proximal arm-muscle electrical activity and power output, were obtained in a mock-u ...[more]

PMID: 33679429

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Project description:Background and objectivePrediction of voluntary upper extremity (UE) movement recovery is largely unknown in patients with little voluntary UE movement at admission. The present study aimed to investigate (1) the extent and variation of voluntary UE movement recovery, and (2) the best predictive model of the recovery of voluntary UE movement by clinical variables in patients with severe UE paresis.DesignProspective cohort study.Methods140 (out of 590) stroke patients with severe UE paresis completed all assessments. Voluntary UE movement was assessed using the UE subscale of the Stroke Rehabilitation Assessment of Movement (STREAM-UE). Two outcome measures, STREAM-UE scores at discharge (DC(STREAM-UE)) and changes between admission and discharge (Δ(STREAM-UE)), were investigated to represent the final states and improvement of the recovery of voluntary UE movement. Stepwise regression analyses were used to investigate 19 clinical variables and to find the best predictive models of the two outcome measures.ResultsThe participants showed wide variation in both DC(STREAM-UE) and Δ(STREAM-UE). 3.6% of the participants almost fully recovered at discharge (DC(STREAM-UE) > 15). A large improvement (Δ(STREAM-UE) >= 10) occurred in 16.4% of the participants, while 32.9% of the participants did not have any improvement. The four predictors for the DC(STREAM-UE) (R(2) = 35.0%) were 'baseline STREAM-UE score', 'hemorrhagic stroke', 'baseline National Institutes of Health Stroke Scale (NIHSS) score', and 'cortical lesion excluding primary motor cortex'. The three predictors for the Δ(STREAM-UE) (R(2) = 22.0%) were 'hemorrhagic stroke', 'baseline NIHSS score', and 'cortical lesion excluding primary motor cortex'.ConclusionsRecovery of voluntary UE movement varied widely in patients with severe UE paresis after stroke. The predictive power of clinical variables was poor. Both results indicate the complex nature of voluntary UE movement recovery in patients with severe UE paresis after stroke.

Dataset Information

Magnetic Resonance-Compatible Arm-Crank Ergometry: A New Platform Linking Whole-Body Calorimetry to Upper-Extremity Biomechanics and Arm Muscle Metabolism.

Introduction

Results

Conclusion

Publications

Magnetic Resonance-Compatible Arm-Crank Ergometry: A New Platform Linking Whole-Body Calorimetry to Upper-Extremity Biomechanics and Arm Muscle Metabolism.

Similar Datasets

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