Reliability of upper limb movement quality metrics during everyday tasks

Assessing motor skill progression based on smoothness during integration of a new tool among hairdressers

Skill acquisition is traditionally assessed based on productivity measures, such as Movement Time (MT), which reflect task execution speed. However, movement smoothness may provide additional insights into skill progression by assessing improvements in movement execution. This study evaluated the evolution of both smoothness and productivity in hairdressing following a change of tool. Kinematic recordings of 14 professional hairdressers, novice users of Ringless Scissors [RS], were taken in the laboratory over four half-days of initiation and after 4.5 months of use in the hair salon. Three types of cuts were performed with Traditional Scissors [TS], then with RS. Smoothness [Number of Peaks (NoP); Log DimensionLess Jerk (LDLJ); SPectral ARC length (SPARC)] was assessed for an elementary movement sequence, spanning tool transport to the start of cutting. MT, representing the duration of these sequences, was assessed as a measure of productivity. After introduction of the RS, smoothness decreased and MT increased. With practice, both characteristics improved. After training, SPARC showed comparable smoothness between RS and TS for two of three cutting movements, while LDLJ and NoP remained higher with TS. After 4.5 months, smoothness improved further, with LDLJ and NoP approaching TS values. Although MT was significantly reduced, it remained higher with RS than TS after 4.5 months use in the salon. These results suggest that introduction of a new tool affects not only productivity - MT - but also movement quality - smoothness. The results presented highlight the relevance of smoothness measures in occupational contexts involving motor learning.

Motion Smoothness Analysis of the Gait Cycle, Segmented by Stride and Associated with the Inertial Sensors' Locations

Portable monitoring devices based on Inertial Measurement Units (IMUs) have the potential to serve as quantitative assessments of human movement. This article proposes a new method to identify the optimal placements of the IMUs and quantify the smoothness of the gait. First, it identifies gait events: foot-strike (FS) and foot-off (FO). Second, it segments the signals of linear acceleration and angular velocities obtained from the IMUs at four locations into steps and strides. Finally, it applies three smoothness metrics (SPARC, PM, and LDLJ) to determine the most reliable metric and the best location for the sensor, using data from 20 healthy subjects who walked an average of 25 steps on a flat surface for this study (117 measurements were processed). All events were identified with less than a 2% difference from those obtained with the photogrammetry system. The smoothness metric with the least variance in all measurements was SPARC. For the smoothness metrics with the least variance, we found significant differences between applying the metrics with the complete signal (C) and the signal segmented by strides (S). This method is practical, time-effective, and low-cost in terms of computation. Furthermore, it is shown that analyzing gait signals segmented by strides provides more information about gait progression.

Comparative analysis of upper body kinematics in stroke, Parkinson's disease, and healthy subjects: An observational study using IMU-based targeted box and block test

BACKGROUND

The Box and Block Test (BBT) is an essential and widely used test in rehabilitation for the assessment of gross unilateral manual dexterity. Although it is a valid, simple, and ecological instrument, it does not provide a quantitative measure of the upper limb trajectories during the test.

RESEARCH QUESTION

The study introduces a new motion-capture-based method (using ecological Inertial Measurement Units - IMUs) to evaluate upper body kinematics while performing a targeted version of BBT (tBBT).

METHODS

This observational study compares data from 35 healthy subjects, 35 subjects with Parkinson's disease, and 35 post-stroke individuals to evaluate upper limb kinematics during tBBT quantitatively. Seven IMUs were placed on the trunk, head, and upper limb of each subject. The joint angles and kinematic scores were calculated and analyzed. Motor task execution time and kinematic scores were statistically correlated with clinical assessment measures. Kruskal-Wallis between groups test and Dunn-Bonferroni post-hoc were used.

RESULTS

The statistics revealed significant differences (p<0.05) among the three groups. The analyzed joint angles highlight various compensatory strategies in neurological subjects, such as using the trunk to complete a motor task instead of the shoulder and using the wrist instead of the elbow, along with differences in movement fluidity (DimensionLess-Jerk, p<0.05). A positive correlation was found between kinematics and the Fugl-Meyer Assessment-Upper Limb (r=0.7344; p<0.01), and a negative correlation between kinematics and the Unified Parkinson's Disease Rating Scale (r=-0.5286; p<0.01).

SIGNIFICANCE

The quantitative assessments of joint kinematics correlated to clinical assessments could guarantee a new method of assessment of the upper limb in subjects with motor deficits. This would allow to capture new insight into the characteristics of the subject's disability, with implications for the choice of a personalized rehabilitation treatment focused on the motor recovery of the upper limb.

Comparison of inter-joint coordination strategies during activities of daily living with prosthetic and anatomical limbs

While healthy individuals have redundant degrees of freedom of the joints, they coordinate their multi-joint movements such that the redundancy is effectively reduced. Achieving high inter-joint coordination may be difficult for upper limb prosthesis users due to the lack of proprioceptive feedback and limited motion of the terminal device. This study compared inter-joint coordination between prosthesis users and individuals without limb loss during different upper limb activities of daily living (ADLs). Nine unilateral prosthesis users (five males) and nine age- and sex-matched controls without limb loss completed three unilateral and three bilateral ADLs. Principal component analysis was applied to the three-dimensional motion trajectories of the trunk and arms to identify coordinative patterns. For each ADL, we quantified the cumulative variance accounted for (VAF) of the first five principal components (pcs), which was the lowest number of pcs that could achieve 90% VAF in control limb movements across all ADLs (5 ≤ n ≤ 9). The VAF was lower for movements involving a prosthesis compared to those completed by controls across all ADLs (p < 0.001). The pc waveforms were similar between movements involving a prosthesis and movements completed by control participants for pc1 (r > 0.78, p < 0.001). The magnitude of the relationship for pc2 and pc3 differed between ADLs, with the strongest correlation for symmetric bilateral ADLs (0.67 ≤ r ≤ 0.97, p < 0.001). Collectively, this study demonstrates that activities of daily living were completed with distinct coordination strategies in prosthesis users compared to individuals without limb loss. Future work should explore how device features, such as the availability of sensory feedback or motorized wrist joints influence multi-joint coordination.

Measurement properties of movement smoothness metrics for upper limb reaching movements in people with moderate to severe subacute stroke

BACKGROUND

Movement smoothness is a potential kinematic biomarker of upper extremity (UE) movement quality and recovery after stroke; however, the measurement properties of available smoothness metrics have been poorly assessed in this group. We aimed to measure the reliability, responsiveness and construct validity of several smoothness metrics.

METHODS

This ancillary study of the REM-AVC trial included 31 participants with hemiparesis in the subacute phase of stroke (median time since stroke: 38 days). Assessments performed at inclusion (Day 0, D0) and at the end of a rehabilitation program (Day 30, D30) included the UE Fugl Meyer Assessment (UE-FMA), the Action Research Arm Test (ARAT), and 3D motion analysis of the UE during three reach-to-point movements at a self-selected speed to a target located in front at shoulder height and at 90% of arm length. Four smoothness metrics were computed: a frequency domain smoothness metric, spectral arc length metric (SPARC); and three temporal domain smoothness metrics (TDSM): log dimensionless jerk (LDLJ); number of submovements (nSUB); and normalized average rectified jerk (NARJ).

RESULTS

At D30, large clinical and kinematic improvements were observed. Only SPARC and LDLJ had an excellent reliability (intra-class correlation > 0.9) and a low measurement error (coefficient of variation < 10%). SPARC was responsive to changes in movement straightness (rSpearman=0.64) and to a lesser extent to changes in movement duration (rSpearman=0.51) while TDSM were very responsive to changes in movement duration (rSpearman>0.8) and not to changes in movement straightness (non-significant correlations). Most construct validity hypotheses tested were verified except for TDSM with low correlations with clinical metrics at D0 (rSpearman<0.5), ensuing low predictive validity with clinical metrics at D30 (non-significant correlations).

CONCLUSIONS

Responsiveness and construct validity of TDSM were hindered by movement duration and/or noise-sensitivity. Based on the present results and concordant literature, we recommend using SPARC rather than TDSM in reaching movements of uncontrolled duration in individuals with spastic paresis after stroke.

TRIAL REGISTRATION

NCT01383512, https://clinicaltrials.gov/ , June 27, 2011.

Resist-as-Needed ADL Training With SPINDLE for Patients With Tremor

Individuals with neurological disorders often exhibit altered manual dexterity and muscle weakness in their upper limbs. These motor impairments with tremor lead to severe difficulties in performing Activities of Daily Living (ADL). There is a critical need for ADL-focused robotic training that improves individual's strength when engaging with dexterous ADL tasks. This research introduces a new approach to training ADLs by employing a novel robotic rehabilitation system, Spherical Parallel INstrument for Daily Living Emulation (SPINDLE), which incorporates Virtual Reality (VR) to simulate ADL tasks. The study results present the feasibility of training individuals with movements similar to ADLs while interacting with the SPINDLE. A new game-based robotic training paradigm is suggested to perform ADL tasks at various intensity levels of resistance as needed. The proposed system can facilitate the training of various ADLs requiring 3-dimensional rotational movements by providing optimal resistance and visual feedback. We envision this system can be utilized as a table-top home device by restoring the impaired motor function of individuals with tremor and muscle weakness, guiding to improved ADL performance and quality of life.

Assessing Spatiotemporal and Quality Alterations in Paretic Upper Limb Movements after Stroke in Routine Care: Proposal and Validation of a Protocol Using IMUs versus MoCap

Accurate assessment of upper-limb movement alterations is a key component of post-stroke follow-up. Motion capture (MoCap) is the gold standard for assessment even in clinical conditions, but it requires a laboratory setting with a relatively complex implementation. Alternatively, inertial measurement units (IMUs) are the subject of growing interest, but their accuracy remains to be challenged. This study aims to assess the minimal detectable change (MDC) between spatiotemporal and quality variables obtained from these IMUs and MoCap, based on a specific protocol of IMU calibration and measurement and on data processing using the dead reckoning method. We also studied the influence of each data processing step on the level of between-system MDC. Fifteen post-stroke hemiparetic subjects performed reach or grasp tasks. The MDC for the movement time, index of curvature, smoothness (studied through the number of submovements), and trunk contribution was equal to 10.83%, 3.62%, 39.62%, and 25.11%, respectively. All calibration and data processing steps played a significant role in increasing the agreement. The between-system MDC values were found to be lower or comparable to the between-session MDC values obtained with MoCap, meaning that our results provide strong evidence that using IMUs with the proposed calibration and processing steps can successfully and accurately assess upper-limb movement alterations after stroke in clinical routine care conditions.

A Comparison of Approaches for Segmenting the Reaching and Targeting Motion Primitives in Functional Upper Extremity Reaching Tasks

There is growing interest in the kinematic analysis of human functional upper extremity movement (FUEM) for applications such as health monitoring and rehabilitation. Deconstructing functional movements into activities, actions, and primitives is a necessary procedure for many of these kinematic analyses. Advances in machine learning have led to progress in human activity and action recognition. However, their utility for analyzing the FUEM primitives of reaching and targeting during reach-to-grasp and reach-to-point tasks remains limited. Domain experts use a variety of methods for segmenting the reaching and targeting motion primitives, such as kinematic thresholds, with no consensus on what methods are best to use. Additionally, current studies are small enough that segmentation results can be manually inspected for correctness. As interest in FUEM kinematic analysis expands, such as in the clinic, the amount of data needing segmentation will likely exceed the capacity of existing segmentation workflows used in research laboratories, requiring new methods and workflows for making segmentation less cumbersome. This paper investigates five reaching and targeting motion primitive segmentation methods in two different domains (haptics simulation and real world) and how to evaluate these methods. This work finds that most of the segmentation methods evaluated perform reasonably well given current limitations in our ability to evaluate segmentation results. Furthermore, we propose a method to automatically identify potentially incorrect segmentation results for further review by the human evaluator. Clinical impact: This work supports efforts to automate aspects of processing upper extremity kinematic data used to evaluate reaching and grasping, which will be necessary for more widespread usage in clinical settings.

Computer-assisted approaches for measuring, segmenting, and analyzing functional upper extremity movement: a narrative review of the current state, limitations, and future directions

The analysis of functional upper extremity (UE) movement kinematics has implications across domains such as rehabilitation and evaluating job-related skills. Using movement kinematics to quantify movement quality and skill is a promising area of research but is currently not being used widely due to issues associated with cost and the need for further methodological validation. Recent developments by computationally-oriented research communities have resulted in potentially useful methods for evaluating UE function that may make kinematic analyses easier to perform, generally more accessible, and provide more objective information about movement quality, the importance of which has been highlighted during the COVID-19 pandemic. This narrative review provides an interdisciplinary perspective on the current state of computer-assisted methods for analyzing UE kinematics with a specific focus on how to make kinematic analyses more accessible to domain experts. We find that a variety of methods exist to more easily measure and segment functional UE movement, with a subset of those methods being validated for specific applications. Future directions include developing more robust methods for measurement and segmentation, validating these methods in conjunction with proposed kinematic outcome measures, and studying how to integrate kinematic analyses into domain expert workflows in a way that improves outcomes.

Comparison of Various Smoothness Metrics for Upper Limb Movements in Middle-Aged Healthy Subjects

BACKGOUND

Metrics for movement smoothness include the number of zero-crossings on the acceleration profile (N0C), the log dimensionless jerk (LDLJ), the normalized averaged rectified jerk (NARJ) and the spectral arc length (SPARC). Sensitivity to the handedness and movement type of these four metrics was compared and correlations with other kinematic parameters were explored in healthy subjects.

METHODS

Thirty-two healthy participants underwent 3D upper limb motion analysis during two sets of pointing movements on each side. They performed forward- and backward-pointing movements at a self-selected speed to a target located ahead at shoulder height and at 90% arm length, with and without a three-second pause between forward and backward movements. Kinematics were collected, and smoothness metrics were computed.

RESULTS

LDLJ, NARJ and N0C found backward movements to be smoother, while SPARC found the opposite. Inter- and intra-subject coefficients of variation were lowest for SPARC. LDLJ, NARJ and N0C were correlated with each other and with movement time, unlike SPARC.

CONCLUSION

There are major differences between smoothness metrics measured in the temporal domain (N0C, LDLJ, NARJ), which depend on movement time, and those measured in the frequency domain, the SPARC, which gave results opposite to the other metrics when comparing backward and forward movements.

Assessing Smoothness of Arm Movements With Jerk: A Comparison of Laterality, Contraction Mode and Plane of Elevation. A Pilot Study

Measuring the quality of movement is a need and a challenge for clinicians. Jerk, defined as the quantity of acceleration variation, is a kinematic parameter used to assess the smoothness of movement. We aimed to assess and compare jerk metrics in asymptomatic participants for 3 important movement characteristics that are considered by clinicians during shoulder examination: dominant and non-dominant side, concentric and eccentric contraction mode, and arm elevation plane. In this pilot study, we measured jerk metrics by using Xsens^® inertial measurement units strapped to the wrists for 11 different active arm movements (ascending and lowering phases): 3 bilateral maximal arm elevations in sagittal, scapular and frontal plane; 2 unilateral functional movements (hair combing and low back washing); and 2 unilateral maximal arm elevations in sagittal and scapular plane, performed with both arms alternately, right arm first. Each arm movement was repeated 3 times successively and the whole procedure was performed 3 times on different days. The recorded time series was segmented with semi-supervised algorithms. Comparisons involved the Wilcoxon signed rank test (p < 0.05) with Bonferroni correction. We included 30 right-handed asymptomatic individuals [17 men, mean (SD) age 31.9 (11.4) years]. Right jerk was significantly less than left jerk for bilateral arm elevations in all planes (all p < 0.05) and for functional movement (p < 0.05). Jerk was significantly reduced during the concentric (ascending) phase than eccentric (lowering) phase for bilateral and unilateral right and left arm elevations in all planes (all p < 0.05). Jerk during bilateral arm elevation was significantly reduced in the sagittal and scapular planes versus the frontal plane (both p < 0.01) and in the sagittal versus scapular plane (p < 0.05). Jerk during unilateral left arm elevation was significantly reduced in the sagittal versus scapular plane (p < 0.05). Jerk metrics did not differ between sagittal and scapular unilateral right arm elevation. Using inertial measurement units, jerk metrics can well describe differences between the dominant and non-dominant arm, concentric and eccentric modes and planes in arm elevation. Jerk metrics were reduced during arm movements performed with the dominant right arm during the concentric phase and in the sagittal plane. Using IMUs, jerk metrics are a promising method to assess the quality of basic shoulder movement.

Sensor Network for Analyzing Upper Body Strategies in Parkinson's Disease versus Normative Kinematic Patterns

In rehabilitation, the upper limb function is generally assessed using clinical scales and functional motor tests. Although the Box and Block Test (BBT) is commonly used for its simplicity and ease of execution, it does not provide a quantitative measure of movement quality. This study proposes the integration of an ecological Inertial Measurement Units (IMUs) system for analysis of the upper body kinematics during the execution of a targeted version of BBT, by able-bodied persons with subjects with Parkinson's disease (PD). Joint angle parameters (mean angle and range of execution) and hand trajectory kinematic indices (mean velocity, mean acceleration, and dimensionless jerk) were calculated from the data acquired by a network of seven IMUs. The sensors were applied on the trunk, head, and upper limb in order to characterize the motor strategy used during the execution of BBT. Statistics revealed significant differences (p < 0.05) between the two groups, showing compensatory strategies in subjects with PD. The proposed IMU-based targeted BBT protocol allows to assess the upper limb function during manual dexterity tasks and could be used in the future for assessing the efficacy of rehabilitative treatments.

Differences in quality of movements made with body-powered and myoelectric prostheses during activities of daily living

BACKGROUND

Upper limb prostheses likely do not enable movements having the same kinematic characteristics as anatomical limbs. The quality of movements made using body-powered and myoelectric prostheses may further differ based on the availability of sensory feedback and method of terminal device actuation. The purpose of this work was to compare the quality of movements made with body-powered and myoelectric prostheses during activities of daily living.

METHODS

Nine transradial body-powered and/or myoelectric prosthesis users and nine controls without limb loss performed six activities of daily living. Movement quality, defined as duration, straightness, and smoothness, for the reaching and manipulation phases was compared between prostheses, as well as prostheses and anatomical limbs.

FINDINGS

The quality of reaching movements were generally similar between prostheses. However, movements with body-powered prostheses were slower (P = 0.007) and less smooth (P < 0.001) when reaching to a deodorant stick and movements with myoelectric prostheses were slower when reaching to place a pin on a corkboard (P = 0.023). Movements with myoelectric prostheses were slower (P ≤ 0.021) and less smooth (P ≤ 0.012) than those with body-powered prostheses during object manipulation, but these differences were not present for all tasks. Movements with prostheses were slower, more curved, and less smooth compared to those with anatomical limbs.

INTERPRETATION

Differences in the quality of movements made with body-powered and myoelectric prostheses primarily occur during object manipulation, rather than reaching. These differences do not exist for all tasks, suggesting that neither prosthesis type offers an absolute advantage in terms of movement quality.

Spatial, But Not Temporal, Kinematics of Spontaneous Upper Extremity Movements Are Related to Gross and Fine Motor Skill Attainment in Infancy

Background: Spontaneous upper extremity movements in infancy provide insight on neuromotor development. Spatiotemporal kinematics have been used to evaluate typical development of reaching, a foundational motor skill in infancy. This study evaluates the relationship between spontaneous upper extremity movements, not elicited by a toy, and motor skill attainment. Methods: N = 12 healthy infants (2–8 months) participated in this longitudinal study (one to four sessions). Motor skills were assessed with the Bayley Scales of Infant and Toddler Development, 3rd Edition: gross motor subtest (GM) and fine motor subtest. Spontaneous upper extremity movements were collected using 3D motion capture technology. Infants were placed in supine for three to twelve 30-s trials, and their movements were recorded. Repeated measure correlation coefficients (Rmcorr) were used to evaluate relationships between variables. Results: There were significant, moderate, positive relationships between the straight distance from start to end of a movement and (a) fine motor score (Rmcorr = .55, p = .03), (b) GM score (Rmcorr = .63, p = .01), and (c) age (Rmcorr = .56, p = .02). There was a significant, moderate, negative relationship between straightness ratio and GM score (Rmcorr = −.52, p = .047). Discussion: Fine and GM skills are related to the straight distance from start to end of a movement and the straightness ratio of underlying spontaneous upper extremity movements.

A new child-friendly 3D bimanual protocol to assess upper limb movement in children with unilateral cerebral palsy: Development and validation

Unilateral cerebral palsy (uCP) causes upper limb movement disorders that impact on daily activities, especially in bimanual condition. However, a few studies have proposed bimanual tasks for 3D motion analysis. The aim of this study was to validate the new version of a child-friendly, 3D, bimanual protocol for the measurement of joint angles and movement quality variables. Twenty children with uCP and 20 typically developing children (TDC) performed the five-task protocol integrated into a game scenario. Each task specifically targeted one or two upper limb degrees of freedom. Joint angles, smoothness and trajectory straightness were calculated. Elbow extension, supination, wrist extension and adduction amplitudes were reduced; hand trajectories were less smooth and straight in children with uCP compared to TDC. Correlations between the performance-based score and kinematic variables were strong. High within and between-session reliability was found for most joint angle variables and lower reliability was found for smoothness and straightness in most tasks. The results therefore demonstrated the validity and reliability of the new protocol for the objective assessment of bimanual function in children with uCP. The evaluation of both joint angles and movement quality variables should increase understanding of pathological movement patterns and help clinicians to optimize treatment. ClinicalTrials.gov identifier: NCT03888443.

Characterizing Functional Upper Extremity Movement in Haptic Virtual Environments

Haptic virtual environments have been used to assess cognitive and fine motor function. For tasks performed in physical environments, upper extremity movement is usually separated into reaching and object manipulation phases using fixed velocity thresholds. However, these thresholds can result in premature segmentation due to additional trajectory adjustments common in virtual environments. In this work, we address the issues of premature segmentation and the lack of a measure to characterize the spatial distribution of a trajectory while targeting an object. We propose a combined relative distance and velocity segmentation procedure and use principal component analysis (PCA) to capture the spatial distribution of the participant's targeting phase. Synthetic data and 3D motion data from twenty healthy adults were used to evaluate the methods with positive results. We found that these methods quantify motor skill improvement of healthy participants performing repeated trials of a haptic virtual environment task.