Maxime Térémetz

Upper Limb Outcome Measures Used in Stroke Rehabilitation Studies: A Systematic Literature Review.

Background Establishing which upper limb outcome measures are most commonly used in stroke studies may help in improving consensus among scientists and clinicians. Objective In this study we aimed to identify the most commonly used upper limb outcome measures in intervention studies after stroke and to describe domains covered according to ICF, how measures are combined, and how their use varies geographically and over time. Methods Pubmed, CinHAL, and PeDRO databases were searched for upper limb intervention studies in stroke according to PRISMA guidelines and477 studies were included. Results In studies 48different outcome measures were found. Only 15 of these outcome measures were used in more than 5% of the studies. The Fugl-Meyer Test (FMT)was the most commonly used measure (in 36% of studies). Commonly used measures covered ICF domains of body function and activity to varying extents. Most studies (72%) combined multiple outcome measures: the FMT was often combined with the Motor Activity Log (MAL), the Wolf Motor Function Test and the Action Research Arm Test, but infrequently combined with the Motor Assessment Scale or the Nine Hole Peg Test. Key components of manual dexterity such as selective finger movements were rarely measured. Frequency of use increased over a twelve-year period for the FMT and for assessments of kinematics, whereas other measures, such as the MAL and the Jebsen Taylor Hand Test showed decreased use over time. Use varied largely between countries showing low international consensus. Conclusions The results showed a large diversity of outcome measures used across studies. However, a growing number of studies used the FMT, a neurological test with good psychometric properties. For thorough assessment the FMT needs to be combined with functional measures. These findings illustrate the need for strategies to build international consensus on appropriate outcome measures for upper limb function after stroke.

A novel method for the quantification of key components of manual dexterity after stroke

BackgroundA high degree of manual dexterity is a central feature of the human upper limb. A rich interplay of sensory and motor components in the hand and fingers allows for independent control of fingers in terms of timing, kinematics and force. Stroke often leads to impaired hand function and decreased manual dexterity, limiting activities of daily living and impacting quality of life. Clinically, there is a lack of quantitative multi-dimensional measures of manual dexterity. We therefore developed the Finger Force Manipulandum (FFM), which allows quantification of key components of manual dexterity. The purpose of this study was (i) to test the feasibility of using the FFM to measure key components of manual dexterity in hemiparetic stroke patients, (ii) to compare differences in dexterity components between stroke patients and controls, and (iii) to describe individual profiles of dexterity components in stroke patients.Methods10 stroke patients with mild-to-moderate hemiparesis and 10 healthy subjects were recruited. Clinical measures of hand function included the Action Research Arm Test and the Moberg Pick-Up Test. Four FFM tasks were used: (1) Finger Force Tracking to measure force control, (2) Sequential Finger Tapping to measure the ability to perform motor sequences, (3) Single Finger Tapping to measure timing effects, and (4) Multi-Finger Tapping to measure the ability to selectively move fingers in specified combinations (independence of finger movements).ResultsMost stroke patients could perform the tracking task, as well as the single and multi-finger tapping tasks. However, only four patients performed the sequence task. Patients showed less accurate force control, reduced tapping rate, and reduced independence of finger movements compared to controls. Unwanted (erroneous) finger taps and overflow to non-tapping fingers were increased in patients. Dexterity components were not systematically related among each other, resulting in individually different profiles of deficient dexterity. Some of the FFM measures correlated with clinical scores.ConclusionsQuantifying some of the key components of manual dexterity with the FFM is feasible in moderately affected hemiparetic patients. The FFM can detect group differences and individual profiles of deficient dexterity. The FFM is a promising tool for the measurement of key components of manual dexterity after stroke and could allow improved targeting of motor rehabilitation.

Impaired force control in writer's cramp showing a bilateral deficit in sensorimotor integration.

Abnormal cortical processing of sensory inputs has been found bilaterally in writers cramp (WC). This study tested the hypothesis that patients with WC have an impaired ability to adjust grip forces according to visual and somatosensory cues in both hands.

Deficient grip force control in schizophrenia: behavioral and modeling evidence for altered motor inhibition and motor noise.

Whether upper limb sensorimotor control is affected in schizophrenia and how underlying pathological mechanisms may potentially intervene in these deficits is still being debated. We tested voluntary force control in schizophrenia patients and used a computational model in order to elucidate potential cerebral mechanisms underlying sensorimotor deficits in schizophrenia. A visuomotor grip force-tracking task was performed by 17 medicated and 6 non-medicated patients with schizophrenia (DSM-IV) and by 15 healthy controls. Target forces in the ramp-hold-and-release paradigm were set to 5N and to 10% maximal voluntary grip force. Force trajectory was analyzed by performance measures and Principal Component Analysis (PCA). A computational model incorporating neural control signals was used to replicate the empirically observed motor behavior and to explore underlying neural mechanisms. Grip task performance was significantly lower in medicated and non-medicated schizophrenia patients compared to controls. Three behavioral variables were significantly higher in both patient groups: tracking error (by 50%), coefficient of variation of force (by 57%) and duration of force release (up by 37%). Behavioral performance did not differ between patient groups. Computational simulation successfully replicated these findings and predicted that decreased motor inhibition, together with an increased signal-dependent motor noise, are sufficient to explain the observed motor deficits in patients. PCA also suggested altered motor inhibition as a key factor differentiating patients from control subjects: the principal component representing inhibition correlated with clinical severity. These findings show that schizophrenia affects voluntary sensorimotor control of the hand independent of medication, and suggest that reduced motor inhibition and increased signal-dependent motor noise likely reflect key pathological mechanisms of the sensorimotor deficit.

Manual Dexterity in Schizophrenia—A Neglected Clinical Marker?

Impaired manual dexterity is commonly observed in schizophrenia. However, a quantitative description of key sensorimotor components contributing to impaired dexterity is lacking. Whether the key components of dexterity are differentially affected and how they relate to clinical characteristics also remains unclear. We quantified the degree of dexterity in 35 stabilized patients with schizophrenia and in 20 age-matched control subjects using four visuomotor tasks: (i) force tracking to quantify visuomotor precision, (ii) sequential finger tapping to measure motor sequence recall, (iii) single-finger tapping to assess temporal regularity, and (iv) multi-finger tapping to measure independence of finger movements. Diverse clinical and neuropsychological tests were also applied. A patient subgroup (N = 15) participated in a 14-week cognitive remediation protocol and was assessed before and after remediation. Compared to control subjects, patients with schizophrenia showed greater error in force tracking, poorer recall of tapping sequences, decreased tapping regularity, and reduced degree of finger individuation. A composite performance measure discriminated patients from controls with sensitivity = 0.79 and specificity = 0.9. Aside from force-tracking error, no other dexterity components correlated with antipsychotic medication. In patients, some dexterity components correlated with neurological soft signs, Positive and Negative Syndrome Scale (PANSS), or neuropsychological scores. This suggests differential cognitive contributions to these components. Cognitive remediation lead to significant improvement in PANSS, tracking error, and sequence recall (without change in medication). These findings show that multiple aspects of sensorimotor control contribute to impaired manual dexterity in schizophrenia. Only visuomotor precision was related to antipsychotic medication. Good diagnostic accuracy and responsiveness to treatment suggest that manual dexterity may represent a useful clinical marker in schizophrenia.