Wearable-based electronics to objectively support diagnosis of motor impairments in school-aged children

Which outcomes are key to the pre-intervention assessment profile of a child with developmental coordination disorder? A systematic review and meta-analysis

BACKGROUND

Purpose of this study was to determine what key aspects of function should be incorporated to make up a pre-intervention assessment profile of a child with Developmental Coordination Disorder (DCD); more specifically, what aspects of functioning are implicated in DCD and what is their relative impact?

METHODS

A systematic review and meta-analysis were conducted, for which Pubmed, Web of Science, Scopus and Proquest were searched (last update: April 2023, PROSPERO: CRD42023461619). Case-control studies were included to determine point estimates for performances on field-based tests in different domains of functioning. Risk of bias was assessed, and level of evidence estimated. Random-effect meta-analyses were performed to calculate the pooled standardized mean differences for domains of functioning and subgrouping was done for clinically relevant subdomains. Heterogeneity was determined with I2.

RESULTS

121 papers were included for analyses. Data of 5 923 children with DCD were included (59.8% boys) and 23 619 Typically Developing (TD) children (45.8% boys). The mean (SD) age of the DCD group was 10.3y (1.2) and 9.3y (1.3) for the TD children. Moderate evidence was found for motor performance, executive functions, sensory processing and perceptions, cognitive functions and sports and leisure activities to be affected in children with DCD.

CONCLUSION

Differences between the two groups varied per domain of functioning. This emphasizes the diversity present within children with DCD and provides a rationale for explaining the heterogeneity in this patient group. Yet, results highlight the potential involvement of all these domains and call for clinicians to be alert not only to examine motor skill difficulties but also other aspects of function. Results indicate the need to develop an individualized pre-intervention multi-dimensional assessment profile for each child with DCD. It also supports the important role that clinicians play in an interdisciplinary team to tackle the difficulties encountered by children with DCD.

A Wearable Diagnostic Assessment System vs. SNAP-IV for the auxiliary diagnosis of ADHD: a diagnostic test

OBJECTIVE

We design a diagnostic test to evaluate the effectiveness and accuracy of A non-intrusive Wearable Diagnostic Assessment System versus SNAP-IV for auxiliary diagnosis of children with ADHD.

METHODS

This study included 55 children aged 6-16 years who were clinically diagnosed with ADHD by DSM-5, and 55 healthy children (typically developing). Each subject completes 10 tasks on the WeDA system (Wearable Diagnostic Assessment System) and Parents of each subject complete the SNAP-IV scale. We will calculate the validity indexes, including sensitivity, specificity, Youden's index, likelihood ratio, and other indexes including predictive value, diagnostic odds ratio, diagnostic accuracy and area under the curve [AUC] to assess the effectiveness of the WeDA system as well as the SNAP-IV.

RESULTS

The sensitivity (94.55% vs. 76.36%) and the specificity (98.18% vs. 80.36%) of the WeDA system were significantly higher than the SNAP-IV. The AUC of the WeDA system (0.964) was higher than the SNAP-IV (0.907). There is non-statistically significant difference between groups (p = 0.068), and both of them have high diagnostic accuracy. In addition, the diagnostic efficacy of the WeDA system was higher than that of SNAP-IV in terms of the Youden index, diagnostic accuracy, likelihood ratio, diagnostic odds ratio and predictive value.

CONCLUSION

The advantages of the WeDA system in terms of diagnostic objectivity, scientific design and ease of operation make it a promising system for widespread use in clinical practice.

Performance Index for in Home Assessment of Motion Abilities in Ataxia Telangiectasia: A Pilot Study

Background. It has been shown in the very recent literature that human walking generates rhythmic motor patterns with hidden time harmonic structures that are represented (at the subject’s comfortable speed) by the occurrence of the golden ratio as the the ratio of the durations of specific walking gait subphases. Such harmonic proportions may be affected—partially or even totally destroyed—by several neurological and/or systemic disorders, thus drastically reducing the smooth, graceful, and melodic flow of movements and altering gait self-similarities. Aim. In this paper we aim at, preliminarily, showing the reliability of a technologically assisted methodology—performed with an easy to use wearable motion capture system—for the evaluation of motion abilities in Ataxia-Telangiectasia (AT), a rare infantile onset neurodegenerative disorder, whose typical neurological manifestations include progressive gait unbalance and the disturbance of motor coordination. Methods. Such an experimental methodology relies, for the first time, on the most recent accurate and objective outcome measures of gait recursivity and harmonicity and symmetry and double support subphase consistency, applied to three AT patients with different ranges of AT severity. Results. The quantification of the level of the distortions of harmonic temporal proportions is shown to include the qualitative evaluations of the three AT patients provided by clinicians. Conclusions. Easy to use wearable motion capture systems might be used to evaluate AT motion abilities through recursivity and harmonicity and symmetry (quantitative) outcome measures.

The impact of wearable electronics in assessing the effectiveness of levodopa treatment in Parkinsons disease

OBJECTIVE

In order to evaluate Parkinson disease patients response to therapeutic interventions, sources of information are mainly patient reports and clinicians assessment of motor functions. However, these sources can suffer from patients subjectivity and from inter/intra raters score variability. Our work aimed at determining the impact of wearable electronics and data analysis in objectifying the effectiveness of levodopa treatment.

METHODS

Seven motor tasks performed by thirty-six patients were measured by wearable electronics and related data were analyzed. This was at the time of therapy initiation (T0), and repeated after six (T1) and 12 months (T2). Wearable electronics consisted of inertial measurement units each equipped with 3-axis accelerometer and 3-axis gyroscope, while data analysis of ANOVA and Pearson correlation algorithms, in addition to a support vector machine (SVM) classification.

RESULTS

According to our findings, levodopa-based therapy alters the patients conditions in general, ameliorating something (e.g. bradykinesia), leaving unchanged others (e.g. tremor), but with poor correlation to the levodopa dose.

CONCLUSION

A technology-based approach can objectively assess levodopa-based therapy effectiveness.

SIGNIFICANCE

Novel devices can improve the accuracy of the assessment of motor function, by integrating the clinical evaluation and patient reports.

Gaming Technology for Pediatric Neurorehabilitation: A Systematic Review

INTRODUCTION

The emergence of gaming technologies, such as videogames and virtual reality, provides a wide variety of possibilities in intensively and enjoyably performing rehabilitation for children with neurological disorders. Solid evidence-based results are however required to promote the use of different gaming technologies in pediatric neurorehabilitation, while simultaneously exploring new related directions concerning neuro-monitoring and rehabilitation in familiar settings.

AIM OF THE STUDY AND METHODS

In order to analyze the state of the art regarding the available gaming technologies for pediatric neurorehabilitation, Scopus and Pubmed Databases have been searched by following: PRISMA statements, PICOs classification, and PEDro scoring.

RESULTS

43 studies have been collected and classified as follows: 11 feasibility studies; six studies proposing home-system solutions; nine studies presenting gamified robotic devices; nine longitudinal intervention trials; and eight reviews. Most of them rely on feasibility or pilot trials characterized by small sample sizes and short durations; different methodologies, outcome assessments and terminologies are involved; the explored spectrum of neurological conditions turns out to be scanty, mainly including the most common and wider debilitating groups of conditions in pediatric neurology: cerebral palsy, brain injuries and autism.

CONCLUSION

Even though it highlights reduced possibilities of drawing evidence-based conclusions due to the above outlined biases, this systematic review raises awareness among pediatricians and other health professionals about gaming technologies. Such a review also points out a definite need of rigorous studies that clearly refer to the underlying neuroscientific principles.

Technology-based therapy-response and prognostic biomarkers in a prospective study of a de novo Parkinson's disease cohort

Early noninvasive reliable biomarkers are among the major unmet needs in Parkinson's disease (PD) to monitor therapy response and disease progression. Objective measures of motor performances could allow phenotyping of subtle, undetectable, early stage motor impairments of PD patients. This work aims at identifying prognostic biomarkers in newly diagnosed PD patients and quantifying therapy-response. Forty de novo PD patients underwent clinical and technology-based kinematic assessments performing motor tasks (MDS-UPDRS part III) to assess tremor, bradykinesia, gait, and postural stability (T0). A visit after 6 months (T1) and a clinical and kinematic assessment after 12 months (T2) where scheduled. A clinical follow-up was provided between 30 and 36 months after the diagnosis (T3). We performed an ANOVA for repeated measures to compare patients' kinematic features at baseline and at T2 to assess therapy response. Pearson correlation test was run between baseline kinematic features and UPDRS III score variation between T0 and T3, to select candidate kinematic prognostic biomarkers. A multiple linear regression model was created to predict the long-term motor outcome using T0 kinematic measures. All motor tasks significantly improved after the dopamine replacement therapy. A significant correlation was found between UPDRS scores variation and some baseline bradykinesia (toe tapping amplitude decrement, p = 0.009) and gait features (velocity of arms and legs, sit-to-stand time, p = 0.007; p = 0.009; p = 0.01, respectively). A linear regression model including four baseline kinematic features could significantly predict the motor outcome (p = 0.000214). Technology-based objective measures represent possible early and reproducible therapy-response and prognostic biomarkers.

Generalized Finite-Length Fibonacci Sequences in Healthy and Pathological Human Walking: Comprehensively Assessing Recursivity, Asymmetry, Consistency, Self-Similarity, and Variability of Gaits

Healthy and pathological human walking are here interpreted, from a temporal point of view, by means of dynamics-on-graph concepts and generalized finite-length Fibonacci sequences. Such sequences, in their most general definition, concern two sets of eight specific time intervals for the newly defined composite gait cycle, which involves two specific couples of overlapping (left and right) gait cycles. The role of the golden ratio, whose occurrence has been experimentally found in the recent literature, is accordingly characterized, without resorting to complex tools from linear algebra. Gait recursivity, self-similarity, and asymmetry (including double support sub-phase consistency) are comprehensively captured. A new gait index, named Φ-bonacci gait number, and a new related experimental conjecture—concerning the position of the foot relative to the tibia—are concurrently proposed. Experimental results on healthy or pathological gaits support the theoretical derivations.

Technology-based methods for the assessment of fine and gross motor skill in children: A systematic overview of available solutions and future steps for effective in-field use

The present review aims at providing researchers and practitioners with a holistic overview of technology-based methods for the assessment of fine and gross motor skill in children. We conducted a search of electronic databases using Web of Science, PubMed and Google Scholar, including studies published up to March 2020, that assessed fine and/or gross motor skills, and utilized technological assessment of varying study design. A total of 739 papers were initially retrieved, and after title/abstract screening, removal of duplicates, and full-text screening, 47 were included. Results suggest that motor skills can be quantitatively estimated using objective methods based on a wearable- and/or laboratory-based technology, for typically developing (TD) and non-TD children. Fine motor skill assessment solutions were; force transducers, instrumented tablets and pens, surface electromyography, and optoelectronic systems. Gross motor skill assessment solutions were; inertial measurements units, optoelectronic systems, baropodometric mats, and force platforms. This review provides a guide in identifying and evaluating the plethora of available technological solutions to motor skill assessment. Although promising, there is still a need for large-scale studies to validate these approaches in terms of accuracy, repeatability, and usability, where interdisciplinary collaborations between researchers and practitioners and transparent reporting practices should be advocated.

Gender differences in instep soccer kicking biomechanics, investigated through a 3D human motion tracker system

BACKGROUND

This study aims at describing and comparing each other male and female soccer players kicking instep a stationary ball. The different measures we collected by the 3D motion capture system Movit G1 and the High-Speed Camera (240 fps) were considered as dependent variables, whereas the gender was considered as the independent one.

METHODS

Twenty soccer well trained non-professional players: 10 men (age: 25.3±6.5 yrs; height 1.80±0.07 m; body mass 76.9±13.2 kg) and 10 women (age: 19±3.34 yrs; height 1.64±0.07 m; body mass 58.2±7.2 kg) volunteered to participate in the study.

RESULTS

Gender differences were found, with a statistical significance (P<0.05) or interesting magnitude (Cohen d>0.5). The most relevant ones were the differences in hip extension of the kicking leg when the foot of the supporting one touches the ground, just before the impact on the ball (independent sample t-Test; P=0.03; Cohen d=1.64) and the speed of the ball, reached immediately after kicking (P<0.001;d=1.23).

CONCLUSIONS

These results, together with the greater pelvic acceleration shown by men compared to women, highlight the need to develop a gender-differentiated training model, in order to customize the kicking technique in women and to reduce the likelihood, currently higher than for men, of kicking related injuries.

Sign Language Recognition Using Wearable Electronics: Implementing k-Nearest Neighbors with Dynamic Time Warping and Convolutional Neural Network Algorithms

We propose a sign language recognition system based on wearable electronics and two different classification algorithms. The wearable electronics were made of a sensory glove and inertial measurement units to gather fingers, wrist, and arm/forearm movements. The classifiers were k-Nearest Neighbors with Dynamic Time Warping (that is a non-parametric method) and Convolutional Neural Networks (that is a parametric method). Ten sign-words were considered from the Italian Sign Language: cose, grazie, maestra, together with words with international meaning such as google, internet, jogging, pizza, television, twitter, and ciao. The signs were repeated one-hundred times each by seven people, five male and two females, aged 29–54 y ± 10.34 (SD). The adopted classifiers performed with an accuracy of 96.6% ± 3.4 (SD) for the k-Nearest Neighbors plus the Dynamic Time Warping and of 98.0% ± 2.0 (SD) for the Convolutional Neural Networks. Our system was made of wearable electronics among the most complete ones, and the classifiers top performed in comparison with other relevant works reported in the literature.

Technology-Based Objective Measures Detect Subclinical Axial Signs in Untreated, de novo Parkinson's Disease

BACKGROUND

Technology-based objective measures (TOMs) recently gained relevance to support clinicians in the assessment of motor function in Parkinson's disease (PD), although limited data are available in the early phases.

OBJECTIVE

To assess motor performances of a population of newly diagnosed, drug free PD patients using wearable inertial sensors and to compare them to healthy controls (HC) and differentiate different PD subtypes [tremor dominant (TD), postural instability gait disability (PIGD), and mixed phenotype (MP)].

METHODS

We enrolled 65 subjects, 36 newly diagnosed, drug-free PD patients and 29 HCs. PD patients were clinically defined as tremor dominant, postural instability-gait difficulties or mixed phenotype. All 65 subjects performed seven MDS-UPDRS III motor tasks wearing inertial sensors: rest tremor, postural tremor, rapid alternating hand movement, foot tapping, heel-to-toe tapping, Timed-Up-and-Go test (TUG) and pull test. The most relevant motor tasks were found combining ReliefF ranking and Kruskal- Wallis feature-selection methods. We used these features, linked to the relevant motor tasks, to highlight differences between PD from HC, by means of Support Vector Machine (SVM) classifier. Furthermore, we adopted SVM to support the relevance of each motor task on the classification accuracy, excluding one task at time.

RESULTS

Motion analysis distinguished PD from HC with an accuracy as high as 97%, based on SVM performed with measured features from tremor and bradykinesia items, pull test and TUG. Heel-to-toe test was the most relevant, followed by TUG and Pull Test.

CONCLUSIONS

In this pilot study, we demonstrate that the SVM algorithm successfully distinguishes de novo drug-free PD patients from HC. Surprisingly, pull test and TUG tests provided relevant features for obtaining high SVM classification accuracy, differing from the report of the experienced examiner. The use of TOMs may improve diagnostic accuracy for these patients.

Wearable Electronics Assess the Effectiveness of Transcranial Direct Current Stimulation on Balance and Gait in Parkinson's Disease Patients

Currently, clinical evaluation represents the primary outcome measure in Parkinson's disease (PD). However, clinical evaluation may underscore some subtle motor impairments, hidden from the visual inspection of examiners. Technology-based objective measures are more frequently utilized to assess motor performance and objectively measure motor dysfunction. Gait and balance impairments, frequent complications in later disease stages, are poorly responsive to classic dopamine-replacement therapy. Although recent findings suggest that transcranial direct current stimulation (tDCS) can have a role in improving motor skills, there is scarce evidence for this, especially considering the difficulty to objectively assess motor function. Therefore, we used wearable electronics to measure motor abilities, and further evaluated the gait and balance features of 10 PD patients, before and (three days and one month) after the tDCS. To assess patients' abilities, we adopted six motor tasks, obtaining 72 meaningful motor features. According to the obtained results, wearable electronics demonstrated to be a valuable tool to measure the treatment response. Meanwhile the improvements from tDCS on gait and balance abilities of PD patients demonstrated to be generally partial and selective.

Assessment of Motor Impairments in Early Untreated Parkinson's Disease Patients: The Wearable Electronics Impact

OBJECTIVE

The complex nature of Parkinson's disease (PD) makes difficult to rate its severity, mainly based on the visual inspection of motor impairments. Wearable sensors have been demonstrated to help overcoming such a difficulty, by providing objective measures of motor abnormalities. However, up to now, those sensors have been used on advanced PD patients with evident motor impairment. As a novelty, here we report the impact of wearable sensors in the evaluation of motor abnormalities in newly diagnosed, untreated, namely de novo, patients.

METHODS

A network of wearable sensors was used to measure motor capabilities, in 30 de novo PD patients and 30 healthy subjects, while performing five motor tasks. Measurement data were used to determine motor features useful to highlight impairments and were compared with the corresponding clinical scores. Three classifiers were used to differentiate PD from healthy subjects.

RESULTS

Motor features gathered from wearable sensors showed a high degree of significance in discriminating the early untreated de novo PD patients from the healthy subjects, with 95% accuracy. The rates of severity obtained from the measured features are partially in agreement with the clinical scores, with some highlighted, though justified, exceptions.

CONCLUSION

Our findings support the feasibility of adopting wearable sensors in the detection of motor anomalies in early, untreated, PD patients.

SIGNIFICANCE

This work demonstrates that subtle motor impairments, occurring in de novo patients, can be evidenced by means of wearable sensors, providing clinicians with instrumental tools as suitable supports for early diagnosis, and subsequent management.