Background and purpose
To support clinical decision‐making in central neurological disorders, a physical examination is used to assess responses to passive muscle stretch. However, what exactly is being assessed is expressed and interpreted in different ways. A clear diagnostic framework is lacking. Therefore, the aim was to arrive at unambiguous terminology about the concepts and measurement around pathophysiological neuromuscular response to passive muscle stretch.
Methods
During two consensus meetings, 37 experts from 12 European countries filled online questionnaires based on a Delphi approach, followed by plenary discussion after rounds. Consensus was reached for agreement ≥75%.
Results
The term hyper‐resistance should be used to describe the phenomenon of impaired neuromuscular response during passive stretch, instead of for example ‘spasticity’ or ‘hypertonia’. From there, it is essential to distinguish non‐neural (tissue‐related) from neural (central nervous system related) contributions to hyper‐resistance. Tissue contributions are elasticity, viscosity and muscle shortening. Neural contributions are velocity dependent stretch hyperreflexia and non‐velocity dependent involuntary background activation. The term ‘spasticity’ should only be used next to stretch hyperreflexia, and ‘stiffness’ next to passive tissue contributions. When joint angle, moment and electromyography are recorded, components of hyper‐resistance within the framework can be quantitatively assessed.
Conclusions
A conceptual framework of pathophysiological responses to passive muscle stretch is defined. This framework can be used in clinical assessment of hyper‐resistance and will improve communication between clinicians. Components within the framework are defined by objective parameters from instrumented assessment. These parameters need experimental validation in order to develop treatment algorithms based on the aetiology of the clinical phenomena.
Background: In stroke rehabilitation not only are the levels of physical activity important, but body postures and movements performed during one’s daily-life are also important. This information is provided by a new one-sensor accelerometer that is commercially available, low-cost, and user-friendly. The present study examines the accuracy of this activity monitor (Activ8) in detecting several classes of body postures and movements in people after a stroke. Methods: Twenty-five people after a stroke participated in an activity protocol with either basic activities or daily-life activities performed in a laboratory and/or at home. Participants wore an Activ8 on their less-affected thigh. The primary outcome was the difference in registered time for the merged class “upright position” (standing/walking/running) between the Activ8 and the video recording (the reference method). Secondary analyses focused on classes other than “upright position”. Results: The Activ8 underestimated the merged class “upright position” by 3.8% (775 s). The secondary analyses showed an overestimation of “lying/sitting” (4.5% (569 s)) and of “cycling” (6.5% (206 s)). The differences were lowest for basic activities in the laboratory and highest for daily-life activities at home. Conclusions: The Activ8 is sufficiently accurate in detecting different classes of body postures and movements of people after a stroke during basic activities and daily-life activities in a laboratory and/or at home.
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