Deans' stroke musings

Changing stroke rehab and research worldwide now.Time is Brain!Just think of all the trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 493 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It's quite disgusting that this information is not available from every stroke association and doctors group.
My back ground story is here:http://oc1dean.blogspot.com/2010/11/my-background-story_8.html

Thursday, February 16, 2017

Effects of Stroke on Ipsilesional End-Effector Kinematics in a Multi-Step Activity of Daily Living

I don't see how anything here will help any stroke survivor get closer to 100% recovery, so go ask your doctor how this will help recovery.
http://journal.frontiersin.org/article/10.3389/fnhum.2017.00042/full?
Philipp Gulde1*, Charmayne Mary Lee Hughes2 and Joachim Hermsdörfer1
  • 1Institute of Movement Science, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
  • 2Department of Kinesiology, San Francisco State University, San Francisco, CA, USA
Background: Stroke frequently impairs activities of daily living (ADL) and deteriorates the function of the contra- as well as the ipsilesional limbs. In order to analyze alterations of higher motor control unaffected by paresis or sensory loss, the kinematics of ipsilesional upper limb movements in patients with stroke has previously been analyzed during prehensile movements and simple tool use actions. By contrast, motion recording of multi-step ADL is rare and patient-control comparisons for movement kinematics are largely lacking. Especially in clinical research, objective quantification of complex externally valid tasks can improve the assessment of neurological impairments.
Methods: In this preliminary study we employed three-dimensional motion recording and applied kinematic analysis in a multi-step ADL (tea-making). The trials were examined with respect to errors and sub-action structure, durations, path lengths (PLs), peak velocities, relative activity (RA) and smoothness. In order to check for specific burdens the sub-actions of the task were extracted and compared. To examine the feasibility of the approach, we determined the behavioral and kinematic metrics of the (ipsilesional) unimanual performance of seven chronic stroke patients (64a ± 11a, 3 with right/4 with left brain damage (LBD), 2 with signs of apraxia, variable severity of paresis) and compared the results with data of 14 neurologically healthy age-matched control participants (70a ± 7a).
Results: T-tests revealed that while the quantity and structure of sub-actions of the task were similar. The analysis of end-effector kinematics was able to detect clear group differences in the associated parameters. Specifically, trial duration (TD) was increased (Cohen’s d = 1.77); the RA (Cohen’s d = 1.72) and the parameters of peak velocities (Cohen’s d = 1.49/1.97) were decreased in the patient group. Analysis of the task’s sub-actions repeated measures analysis of variance (rmANOVA) revealed no impact of the different demands of the sub-actions on the relative performance of the patient group.
Conclusion: The analyses revealed kinematic peculiarities in the performance with the ipsilesional hand. These deficits apparently arose from the cognitive demands like sequencing rather than motor constraints. End-effector kinematics proved as a sensitive method to detect and quantify aspects of disturbed multi-step ADL performance after stroke. If standardized, the examination and the analysis are quick and deliver objective data supporting clinical research.

Introduction

Strokes frequently impair the ability to perform activities of daily living (ADL; Foundas et al., 1995; Forde and Humphreys, 2000; Hartmann et al., 2005; Schwartz, 2006; Wisneski and Johnson, 2007). Stroke related syndromes like apraxia, action disorganization syndrome, hemiparesis and neglect can cause such deficits in ADL. According to a previous estimate 37%–55% of chronic stroke patients are impaired in ADL (Bieńkiewicz et al., 2015).
Following stroke, the behavioral deficits in multi-step ADL arising from impaired action planning are mostly omissions of sub-actions and disorders in the sequencing of subsequent steps, as has been shown in studies on food preparation (Buxbaum, 1998; Schwartz et al., 1999; Bickerton et al., 2007, 2012; Bieńkiewicz et al., 2014), dressing (Sunderland et al., 2006) or hygiene procedures (Humphreys and Forde, 1998). Kinematic analyses do not directly address these types of errors. Kinematics rather quantifies basic aspects of movement execution such as speed, coordination, directness, fluency, smoothness and variability (de los Reyes-Guzmán et al., 2014), although errors can alter kinematic parameters, e.g., the omission of sub-actions can shorten the trajectory of a task or conceptual deficits in handling tools can prolong trial durations (TDs). In this study we consider kinematic measures that can be obtained with only the positional data of the end-effectors.
Up to now, only a few studies employed the approach in the study of multi-step ADL tasks of stroke patients. One investigated scenario is drinking from a glass (Weiss et al., 2000; Alt Murphy et al., 2006, 2011, 2012, 2013; Thies et al., 2009; Kim et al., 2014). Alt Murphy et al. (2011) compared the performance of stroke patients with the performance of age-matched healthy controls. The patients revealed longer movement times, slower peak velocities of the hand and of the elbow (angular peak velocity), a higher number of movement units (less movement smoothness) and an increased trunk displacement when executing the task with their paretic arm. The task was also segmented into five single sub-actions. An analysis of the relative movement times in the different sub-actions showed no differences between healthy subjects and stroke patients indicating that none of the sub-actions was specifically impaired in the patients (Alt Murphy et al., 2011). Notably, parameters representing the patients’ kinematics correlated well with motor function tests like the ARAT, ABILHAND or FMA (Alt Murphy et al., 2012) and reflected changes in motor performance during the first 3 months after a stroke (Alt Murphy et al., 2013). The drinking from a glass task as a multi-step ADL is in comparison to e.g., the tea-making task of moderate complexity (Wood, 1986) since its small set of sub-actions (component complexity) can only be realized in one order (coordinative complexity) and only one of the components changes one of its characteristics (weight of the glass; dynamic complexity).
The present study aimed to examine the feasibility of kinematic parameters when assessing the performance of stroke patients in a complex, multi-step ADL. As a secondary goal we also wanted to gain a better understanding of the reasons underlying impaired ADL performance following stroke. Knowledge of the basic deficits would offer specific targets for interventions in therapy (Bieńkiewicz et al., 2015). Partial results of a pilot of this study have been published in a conference proceeding (Gulde et al., 2014). In order to achieve our main goal we introduced adapted kinematic parameters: relative activity (RA) as a measure of activity, mean peak velocity to describe the average movement speed in tasks with phases of inactivity and number of (velocity) peaks per meter to describe smoothness independent of the amount of executed actions. Such adapted parameters are necessary to analyze irregular signals resulting from the execution of many sub-actions in varying order. The examination of tasks of higher complexity is already being used in the clinical setting, but the assessment is so far qualitative and not quantitative, e.g., trail making tasks or “Multistep Object Use” in the Birmingham Cognitive Screen (BCoS; Bickerton et al., 2012).
The reaction time from the instruction to movement start has been successfully used to quantify the duration of action planning time during simple ADL tasks (Hermsdörfer et al., 2013). During multi-step ADL actions, multiple phases of action planning and movement pauses have to be expected. Consequently, movement pauses were determined with a velocity criterion. The new parameter “RA” resulted, which represents the composition of TD into percentages of activity and inactivity. It is able to indicate prolongations of movement planning and preparation. Such prolongations can be caused by slowed planning of movement trajectories and/or slowed planning of the next action step of a sequence, visual allocation of objects or backwards checking of already performed steps. The second new parameter introduced is the mean peak velocity that quantifies the general movement speed by the average value of action-related velocity peaks.
Considering the literature we expect a number of deviations from normal performance in stroke patients in our ADL-scenario of preparing a cup of tea with milk and sugar, (e.g., Thies et al., 2009; Alt Murphy et al., 2011; Osu et al., 2011; Kim et al., 2014). Due to the, in comparison to e.g., the drinking from a glass task, high complexity (Wood, 1986) of the task (in all three dimensions stated by Wood: component, coordinative and dynamic), we expected the kinematic performance of stroke patients to diverge from the performance of age-matched control subjects. We anticipated increased TDs (Thies et al., 2009; Alt Murphy et al., 2011; Kim et al., 2014) resulting from a reduced movement speed and a higher relative and absolute amount of inactivity. We also expected reduced maximum velocity peaks (Alt Murphy et al., 2011; Osu et al., 2011) and mean peak velocities and reduced movement smoothness (in our study an increased number of (velocity) peaks per meter; Alt Murphy et al., 2011; Osu et al., 2011). Additionally, we hypothesized that path length (PL) may be increased due to sequencing problems and misuse of objects in the patients. Since the sub-actions of the task differ in physical and cognitive demands, we also expected differences in the relative performance of stroke patients in comparison to the age-matched control subjects between the different sub-actions. Such differences can be detected by changes of the relative performance of specific sub-actions (Kim et al., 2014).

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