High-density surface electromyography allows to identify risk conditions and people with and without low back pain during fatiguing frequency-dependent lifting activities

Low back pain (LBP) is a leading cause of disability in the workplace, often caused by manually lifting of heavy loads. Instrumental-based assessment tools are used to quantitatively assess the biomechanical risk of lifting activities. This study aims to verify that, during the execution of fatiguing frequency-dependent lifting, high-density surface electromyography (HDsEMG) allows the discrimination of healthy controls (HC) versus people with LBP and biomechanical risk levels. Fifteen HC and eight people with LBP performed three lifting tasks with a progressively increasing lifting index, each lasting 15 min. Erector spinae (ES) activity was recorded using HDsEMG and amplitude parameters were calculated to characterize the spatial distribution of muscle activity. LBP group showed a less ES activity than HC (lower root mean square across the grid and of the activation region) and an involvement of the same muscular area across the task (lower coefficient of variation of the center of gravity of muscle activity). The results indicate the usefulness of HDsEMG parameters to classify risk levels for both HC and LBP groups and to determine differences between them. The findings suggest that the use of HDsEMG could expand the capabilities of existing instrumental-based tools for biomechanical risk classification during lifting activities.

Gait Analysis in Neurorehabilitation: From Research to Clinical Practice

When brain damage occurs, gait and balance are often impaired. Evaluation of the gait cycle, therefore, has a pivotal role during the rehabilitation path of subjects who suffer from neurological disorders. Gait analysis can be performed through laboratory systems, non-wearable sensors (NWS), and/or wearable sensors (WS). Using these tools, physiotherapists and neurologists have more objective measures of motion function and can plan tailored and specific gait and balance training early to achieve better outcomes and improve patients' quality of life. However, most of these innovative tools are used for research purposes (especially the laboratory systems and NWS), although they deserve more attention in the rehabilitation field, considering their potential in improving clinical practice. In this narrative review, we aimed to summarize the most used gait analysis systems in neurological patients, shedding some light on their clinical value and implications for neurorehabilitation practice.

Innovative Technologies in the Neurorehabilitation of Traumatic Brain Injury: A Systematic Review

Motor and cognitive rehabilitation in individuals with traumatic brain injury (TBI) is a growing field of clinical and research interest. In fact, novel rehabilitative approaches allow a very early verticalization and gait training through robotic devices and other innovative tools boosting neuroplasticity, thanks to the high-intensity, repetitive and task-oriented training. In the same way, cognitive rehabilitation is also evolving towards advanced interventions using virtual reality (VR), computer-based approaches, telerehabilitation and neuromodulation devices. This review aimed to systematically investigate the existing evidence concerning the role of innovative technologies in the motor and cognitive neurorehabilitation of TBI patients. We searched and reviewed the studies published in the Cochrane Library, PEDro, PubMed and Scopus between January 2012 and September 2022. After an accurate screening, only 29 papers were included in this review. This systematic review has demonstrated the beneficial role of innovative technologies when applied to cognitive rehabilitation in patients with TBI, while evidence of their effect on motor rehabilitation in this patient population is poor and still controversial.

Centre of pressure parameters for the assessment of biomechanical risk in fatiguing frequency-dependent lifting activities

Lifting tasks, among manual material handling activities, are those mainly associated with low back pain. In recent years, several instrumental-based tools were developed to quantitatively assess the biomechanical risk during lifting activities. In this study, parameters related to balance and extracted from the Centre of Pressure (CoP) data series are studied in fatiguing frequency-dependent lifting activities to: i) explore the possibility of classifying people with LBP and asymptomatic people during the execution of task; ii) examine the assessment of the risk levels associated with repetitive lifting activities, iii) enhance current understanding of postural control strategies during lifting tasks. Data were recorded from 14 asymptomatic participants and 7 participants with low back pain. The participants performed lifting tasks in three different lifting conditions (with increasing lifting frequency and risk levels) and kinetic and surface electromyography (sEMG) data were acquired. Kinetic data were used to calculated the CoP and parameters extracted from the latter show a discriminant capacity for the groups and the risk levels. Furthermore, sEMG parameters show a trend compatible with myoelectric manifestations of muscular fatigue. Correlation results between sEMG and CoP velocity parameters revealed a positive correlation between amplitude sEMG parameters and CoP velocity in both groups and a negative correlation between frequency sEMG parameters and CoP velocity. The current findings suggest that it is possible to quantitatively assess the risk level when monitoring fatiguing lifting tasks by using CoP parameters as well as identify different motor strategies between people with and without LBP.

Trunk Muscle Coactivation in People with and without Low Back Pain during Fatiguing Frequency-Dependent Lifting Activities

Lifting tasks are manual material-handling activities and are commonly associated with work-related low back disorders. Instrument-based assessment tools are used to quantitatively assess the biomechanical risk associated with lifting activities. This study aims at highlighting different motor strategies in people with and without low back pain (LBP) during fatiguing frequency-dependent lifting tasks by using parameters of muscle coactivation. A total of 15 healthy controls (HC) and eight people with LBP performed three lifting tasks with a progressively increasing lifting index (LI), each lasting 15 min. Bilaterally erector spinae longissimus (ESL) activity and rectus abdominis superior (RAS) were recorded using bipolar surface electromyography systems (sEMG), and the time-varying multi-muscle coactivation function (TMCf) was computed. The TMCf can significantly discriminate each pair of LI and it is higher in LBP than HC. Collectively, our findings suggest that it is possible to identify different motor strategies between people with and without LBP. The main finding shows that LBP, to counteract pain, coactivates the trunk muscles more than HC, thereby adopting a strategy that is stiffer and more fatiguing.

Bipolar versus high-density surface electromyography for evaluating risk in fatiguing frequency-dependent lifting activities

Workers often develop low back pain due to manually lifting heavy loads. Instrumental-based assessment tools are used to quantitatively assess the biomechanical risk in lifting activities. This study aims to verify the hypothesis that high-density surface electromyography (HDsEMG) allows an optimized discrimination of risk levels associated with different fatiguing lifting conditions compared to traditional bipolar sEMG. 15 participants performed three lifting tasks with a progressively increasing lifting index (LI) each lasting 15 min. Erector spinae (ES) activity was recorded using both bipolar and HDsEMG systems. The amplitude of both bipolar and HDsEMG can significantly discriminate each pair of LI. HDsEMG data could discriminate across the different LIs starting from the fourth minute of the task while bipolar sEMG could only do so towards the end. The higher discriminative power of HDsEMG data across the lifting tasks makes such methodology a valuable tool to be used to monitor fatigue while lifting and could extend the possibilities offered by currently available instrumental-based tools.

Kinematic biomarkers of chronic neck pain measured during gait: A data-driven classification approach

People with chronic neck pain (CNP) often present with altered gait kinematics. This paper investigates, combines, and compares the kinematic features from linear and nonlinear walking trajectories to design supervised machine learning models which differentiate asymptomatic individuals from those with CNP. For this, 126 features were extracted from seven body segments of 20 asymptomatic subjects and 20 individuals with non-specific CNP. Neighbourhood Component Analysis (NCA) was used to identify body segments and the corresponding significant features which have the maximum discriminative power for conducting classification. We assessed the efficacy of NCA combined with K- Nearest Neighbour (K-NN), Support Vector Machine and Linear Discriminant Analysis. By applying NCA, all classifiers increased their performance for both linear and nonlinear walking trajectories. Notably, features selected by NCA which magnify the classification power of the computational model were solely from the head, trunk and pelvis kinematics. Our results revealed that the nonlinear trajectory provides the best classification performance through the NCA-K-NN algorithms with an accuracy of 90%, specificity of 100% and sensitivity of 83.3%. The selected features by NCA are introduced as key biomarkers of gait kinematics for classifying non-specific CNP. This paper provides insight into changes in gait kinematics which are present in people with non-specific CNP which can be exploited for classification purposes. The result highlights the importance of curvilinear gait kinematic features which potentially could be utilized in future research to predict recurrent episodes of neck pain.

Influence of low back pain and its remission on motor abundance in a low-load lifting task

Having an abundance of motor solutions during movement may be advantageous for the health of musculoskeletal tissues, given greater load distribution between tissues. The aim of the present study was to understand whether motor abundance differs between people with and without low back pain (LBP) during a low-load lifting task. Motion capture with electromyography (EMG) assessment of 15 muscles was performed on 48 participants [healthy control (con) = 16, remission LBP (rLBP) = 16, current LBP (cLBP) = 16], during lifting. Non-negative matrix factorization and uncontrolled manifold analysis were performed to decompose inter-repetition variability in the temporal activity of muscle modes into goal equivalent (GEV) and non-goal equivalent (NGEV) variabilities in the control of the pelvis and trunk linear displacements. Motor abundance occurs when the ratio of GEV to NGEV exceeds zero. There were significant group differences in the temporal activity of muscle modes, such that both cLBP and rLBP individuals demonstrated greater activity of muscle modes that reflected lumbopelvic coactivation during the lifting phase compared to controls. For motor abundance, there were no significant differences between groups. Individuals with LBP, including those in remission, had similar overall motor abundance, but use different activation profiles of muscle modes than asymptomatic people during lifting.

Controlled manual loading of body tissues: towards the next generation of pressure algometer

Assessing the responses of body tissue subjected to mechanical load is a fundamental component of the clinical examination, psychophysical assessments and bioengineering research. The forces applied during such assessments are usually generated manually, via the hands of the tester, and aimed at discreet tissue sites. It is therefore desirable to objectively quantify and optimise the control of manually applied force. However, current laboratory-grade manual devices and commercial software packages, in particular pressure algometer systems, are generally inflexible and expensive. This paper introduces and discusses several principles that should be implemented as design goals within a flexible, generic software application, given currently available force measurement hardware. We also discuss pitfalls that clinicians and researchers might face when using current pressure algometer systems and provide examples of these. Finally, we present our implementation of a pressure algometer system that achieves these goals in an efficient and affordable way for researchers and clinicians. As part of this effort, we will be sharing our configurable software application via a software repository.

Kinematic Biomarkers of Chronic Neck Pain During Curvilinear Walking: A Data-driven Differential Diagnosis Approach. Annu Int Conf IEEE Eng Med Biol Soc 2020;2020:5162-5166. [PMID: 33019148 DOI: 10.1109/embc44109.2020.9176457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Chronic Neck Pain (CNP) can be associated with biomechanical changes. This paper investigates the changes in patterns of walking kinematics along a curvilinear trajectory and uses a specially designed feature space, coupled with a machine learning framework to conduct a data-driven differential diagnosis, between asymptomatic individuals and those with CNP. For this, 126 kinematic features were collected from seven body segments of 40 participants (20 asymptomatic, 20 individuals with CNP). The features space was processed through a Neighbourhood Component Analysis (NCA) algorithm to systematically select the most significant features which have the maximum discriminative power for conducting the differential diagnosis. The selected features were then processed by a K-Nearest Neighbors (K-NN) classifier to conduct the task. Our results show that, through a systematic selection of feature space, we can significantly increase the classification accuracy. In this regard, a 35% increase is reported after applying the NCA. Thus, we have shown that using only 13 features (of which 61% belong to kinematic features and 39% to statistical features) from five body segments (Head, Trunk, Pelvic, Hip and Knee) we can achieve an accuracy, sensitivity and specificity of 82.50%, 80.95% and 84.21% respectively. This promising result highlights the importance of curvilinear kinematic features through the proposed information processing pipeline for conducting differential diagnosis and could be tested in future studies to predict the likelihood of people developing recurrent neck pain.

Classifying individuals with and without patellofemoral pain syndrome using ground force profiles - Development of a method using functional data boosting

BACKGROUND

Predictors of recovery in patellofemoral pain syndrome (PFPS) currently used in prognostic models are scalar in nature, despite many physiological measures originally lying on the functional scale. Traditional modelling techniques cannot harness the potential predictive value of functional physiological variables.

RESEARCH QUESTION

What is the classification performance of PFPS status of a statistical model when using functional ground reaction force (GRF) time-series?

METHODS

Thirty-one individuals (control = 17, PFPS = 14) performed maximal countermovement jumps, on two force plates. The three-dimensional components of the GRF profiles were time-normalized between the start of the eccentric phase and take-off, and used as functional predictors. A statistical model was developed using functional data boosting (FDboost), for binary classification of PFPS statuses (control vs PFPS). The area under the Receiver Operating Characteristic curve (AUC) was used to quantify the model's ability to discriminate the two groups.

RESULTS

The three predictors of GRF waveform achieved an average out-of-bag AUC of 93.7 %. A 1 % increase in applied medial force reduced the log odds of being in the PFPS group by 0.68 at 87 % of jump cycle. In the AP direction, a 1 % reduction in applied posterior force increased the log odds of being classified as PFPS by 1.10 at 70 % jump cycle. For the vertical GRF, a 1 % increase in applied force reduced the log odds of being classified in the PFPS group by 0.12 at 44 % of the jump cycle.

SIGNIFICANCE

Using simple functional GRF variables collected during functionally relevant task, in conjunction with FDboost, produced clinically interpretable models that retain excellent classification performance in individuals with PFPS. FDboost may be an invaluable tool to be used in longitudinal cohort prognostic studies, especially when scalar and functional predictors are collected.

Individuals with patellofemoral pain syndrome have altered inter-leg force coordination

BACKGROUND

Patellofemoral pain syndrome (PFPS) is one of the most common musculoskeletal disorders. Pain may be further exacerbated by atypical motor coordination strategies. It has been thought that low coordination variability may concentrate loads onto painful knee tissues.

RESEARCH QUESTION

To investigate if inter-limb force coordination is altered between individuals with and without PFPS.

METHODS

31 individuals (control = 17, PFPS = 14) performed bilateral vertical hopping, on two force plates at three frequencies (2.2, 2.6, 3.0 Hz). Uncontrolled manifold analysis (UCM) was used to provide an index of motor abundance (IMA) in the coordination of inter-limb forces to stabilize the two-limb's total force. UCM was applied to the study of forces in each plane (medial-lateral (ML), anterior-posterior (AP), vertical). Bayesian Functional Data Analysis was used for statistical inference. We calculated the mean (u) with 95 % credible interval (CrI) of the difference ΔIMA_con>PFPS between the two groups. We also calculated the probability PΔIMA_con>PFPS>0data).

RESULTS

Individuals with PFPS had the greatest significant decrement from controls at 6% of stance hopping at 2.6 Hz by a mean difference of -0.23 for ML GRF; at 19 % of stance hopping at 2.2 Hz by a mean difference of -0.14 for AP GRF; and 52 % of stance hopping at 2.6 Hz by a mean difference of -0.14 for vertical GRF. For vertical GRF, there was a > 0.95 probability that controls had greater IMA than individuals with PFPS hopping between 12-13% of stance at 2.2 Hz, and between 48-55% at 2.6 Hz.

SIGNIFICANCE

Individuals with PFPS have reduced inter-leg force coordination for impact force attenuation and body support, compared to asymptomatic controls. The present study provides insights into a plausible mechanism underpinning persistent knee pain which could be used in the development of novel rehabilitative approaches for individuals with PFPS.

Interpretable machine learning models for classifying low back pain status using functional physiological variables

PURPOSE

To evaluate the predictive performance of statistical models which distinguishes different low back pain (LBP) sub-types and healthy controls, using as input predictors the time-varying signals of electromyographic and kinematic variables, collected during low-load lifting.

METHODS

Motion capture with electromyography (EMG) assessment was performed on 49 participants [healthy control (con) = 16, remission LBP (rmLBP) = 16, current LBP (LBP) = 17], whilst performing a low-load lifting task, to extract a total of 40 predictors (kinematic and electromyographic variables). Three statistical models were developed using functional data boosting (FDboost), for binary classification of LBP statuses (model 1: con vs. LBP; model 2: con vs. rmLBP; model 3: rmLBP vs. LBP). After removing collinear predictors (i.e. a correlation of > 0.7 with other predictors) and inclusion of the covariate sex, 31 predictors were included for fitting model 1, 31 predictors for model 2, and 32 predictors for model 3.

RESULTS

Seven EMG predictors were selected in model 1 (area under the receiver operator curve [AUC] of 90.4%), nine predictors in model 2 (AUC of 91.2%), and seven predictors in model 3 (AUC of 96.7%). The most influential predictor was the biceps femoris muscle (peak [Formula: see text]  = 0.047) in model 1, the deltoid muscle (peak [Formula: see text] =  0.052) in model 2, and the iliocostalis muscle (peak [Formula: see text] =  0.16) in model 3.

CONCLUSION

The ability to transform time-varying physiological differences into clinical differences could be used in future prospective prognostic research to identify the dominant movement impairments that drive the increased risk. These slides can be retrieved under Electronic Supplementary Material.

Classifying neck pain status using scalar and functional biomechanical variables - development of a method using functional data boosting

BACKGROUND

Individuals with neck pain have different movement and muscular activation (collectively termed as biomechanical variables) patterns compared to healthy individuals. Incorporating biomechanical variables as covariates into prognostic models is challenging due to the high dimensionality of the data.

RESEARCH QUESTION

What is the classification performance of neck pain status of a statistical model which uses both scalar and functional biomechanical covariates?

METHODS

Motion capture with electromyography assessment on the sternocleidomastoid, splenius cervicis, erector spinae, was performed on 21 healthy and 26 individuals with neck pain during walking over three gait conditions (rectilinear, curvilinear clockwise (CW) and counterclockwise (CCW)). After removing highly collinear variables, 94 covariates across the three conditions were used to classify neck pain status using functional data boosting (FDboost).

RESULTS

Two functional covariates trunk lateral flexion angle during CCW gait, and trunk flexion angle during CW gait; and a scalar covariate, hip jerk index during CCW gait were selected. The model achieved an estimated AUC of 80.8 %. For hip jerk index, an increase in hip jerk index by one unit increased the log odds of being in the neck pain group by 0.37. A 1° increase in trunk lateral flexion angle throughout gait alone reduced the probability of being in the neck pain group from 0.5 to 0.15. A 1° increase in trunk flexion angle throughout gait alone increased the probability of being in the neck pain group from 0.5 to 0.9.

SIGNIFICANCE

Interpreting the physiological significance of the extracted covariates, with other biomechanical variables, suggests that individuals with neck pain performed curvilinear walking using a stiffer strategy, compared to controls; and this increased the risk of being in the neck pain group. FDboost can produce clinically interpretable models with complex high dimensional data and could be used in future prognostic modelling studies in neck pain research.

Variability of the helical axis during active cervical movements in people with chronic neck pain

BACKGROUND

Recent work described parameters of the helical axis in asymptomatic people with potential for investigating kinematic changes in the cervical region. This approach could provide novel information on movement variability in people with neck pain, however this has never been investigated. This study aimed to investigate movement variability during active neck movements performed at different speeds in people with and without chronic neck pain.

METHODS

This observational case-control study examined 18 participants with chronic neck pain of either idiopathic or traumatic origin and 18 gender-matched asymptomatic participants. Cervical kinematics were captured with 3D motion capture as people with and without chronic neck pain performed flexion-extension, bilateral lateral flexion and bilateral rotation at different speeds (natural, slow, and fast). The mean distance and mean angle parameters of the helical axis were extracted to describe 3D motion and quantify movement variability.

FINDINGS

A smaller mean distance was observed in those with neck pain compared to the asymptomatic participants during flexion-extension (P = 0.019) and rotation movements (P = 0.007). The neck pain group displayed smaller values for the mean angle during rotation movements with different speeds (P = 0.01). These findings indicate less variable movement for those with neck pain relative to the asymptomatic participants. No difference in the mean angle was observed between groups for flexion-extension and lateral flexion.

INTERPRETATION

The findings reiterate the importance of data derived from kinematic measures, and its potential for providing clinicians with further insight into the quality of active neck movements in people with chronic neck pain.

Surface electromyographic amplitude does not identify differences in neural drive to synergistic muscles

Surface electromyographic (EMG) signal amplitude is typically used to compare the neural drive to muscles. We experimentally investigated this association by studying the motor unit (MU) behavior and action potentials in the vastus medialis (VM) and vastus lateralis (VL) muscles. Eighteen participants performed isometric knee extensions at four target torques [10, 30, 50, and 70% of the maximum torque (MVC)] while high-density EMG signals were recorded from the VM and VL. The absolute EMG amplitude was greater for VM than VL ( P < 0.001), whereas the EMG amplitude normalized with respect to MVC was greater for VL than VM ( P < 0.04). Because differences in EMG amplitude can be due to both differences in the neural drive and in the size of the MU action potentials, we indirectly inferred the neural drives received by the two muscles by estimating the synaptic inputs received by the corresponding motor neuron pools. For this purpose, we analyzed the increase in discharge rate from recruitment to target torque for motor units matched by recruitment threshold in the two muscles. This analysis indicated that the two muscles received similar levels of neural drive. Nonetheless, the size of the MU action potentials was greater for VM than VL ( P < 0.001), and this difference explained most of the differences in EMG amplitude between the two muscles (~63% of explained variance). These results indicate that EMG amplitude, even following normalization, does not reflect the neural drive to synergistic muscles. Moreover, absolute EMG amplitude is mainly explained by the size of MU action potentials.

NEW & NOTEWORTHY Electromyographic (EMG) amplitude is widely used to compare indirectly the strength of neural drive received by synergistic muscles. However, there are no studies validating this approach with motor unit data. Here, we compared between-muscles differences in surface EMG amplitude and motor unit behavior. The results clarify the limitations of surface EMG to interpret differences in neural drive between muscles.

Biofeedback rehabilitation of posture and weightbearing distribution in stroke: a center of foot pressure analysis

Weight bearing on the paretic lower extremity and transfer of weight from one lower extremity to the other are important goals of stroke rehabilitation. Improvements in these limb loading and weight transfer abilities have been shown to relate to improved performance of many functional activities. Unfortunately, valid and practical clinical measures of paretic lower extremity loading and weight transfer have not been identified. The purpose of this study was to quantitatively assess, through center of foot pressure (CoP) analysis of quiet upright stance control, recovery of paretic limb loading as a measure of weight transfer in early stroke subjects, testing the effectiveness of a targeted rehabilitation intervention based on audiovisual biofeedback. Thirty-seven adults with lower extremity motor impairment following unilateral, non-cerebellar stroke, were Biofeedback rehabilitation of posture and weightbearing distribution in stroke: a center of foot pressure analysis tested twice, at an interval of at least one month post stroke and following rehabilitation intervention aimed at correcting their asymmetrical weight bearing. The intervention was performed with (Study Group, SG) or without (Control Group, CG) a postural audio-visual biofeedback approach. Indices of postural stability and of balance control asymmetry were estimated by acquiring the movements of the CoP during quiet upright stance condition with or without visual input (eyes open, EO and eyes closed, EC). Clinical scales were also administered. Both the CG and the SG subjects showed improved control in upright stance posture as documented by significant improvements in the scale scores and indices of stability during both the EO and the EC condition. Only the SG showed a significantly reduced CoP index of asymmetry. The CoP index of asymmetry, correlating with clinical motor scales, is a valid measure of paretic limb loading during stroke recovery. Postural audio-visual biofeedback represented the more effective approach for reducing weight loading asymmetry of the lower limbs in stroke.

Arm weight support training improves functional motor outcome and movement smoothness after stroke

The aim of this study was to compare the effectiveness in acute stroke patients of a rehabilitation program performed with or without an arm weight support device. Twenty-eight acute, first-ever unilateral stroke patients were enrolled in a single-blind, randomized controlled trial. Clinical evaluation included Fugl-Mayer Assessment, Functional Independence Measure and kinematic analysis [maximum and mean hand velocity, maximum range of motion (Max RoM), normalized jerk (NJ)]. Patients received 12 daily 30-minute sessions (6/week) of additional upper limb therapy performed using an arm weight support device (study group) or additional traditional physiotherapy (control group). The patients were evaluated on admission and at the end of the rehabilitation intervention. The two groups were clinically comparable on admission (p>0.05). Both groups showed significant improvements in clinical scale scores and in Max RoM in flexionextension, while only the study group showed improvements in NJ and in Max RoM in adductionabduction. Rehabilitation training using an arm weight support device appears to be a useful method to supplement conventional therapy in acute stroke patients, increasing smoothness of movement and motor function.

Blood biomarkers role in acute ischemic stroke patients: higher is worse or better?

Background

Thrombolytic therapy (TT) for acute ischemic stroke (AIS) can provoke bleeding’s complication depending on the ischemic lesion (IL) dimension. Inflammation involved in the setting of acute ischaemic stroke, is associated with infarct size. We aimed to study the independent correlation and association between clinical panel of routinely identified biomarkers, including inflammatory parameters, and cerebral IL dimension and site.

Results

We evaluated eleven biomarkers in 105 unrelated patients during their hospitalization after acute stroke event. Our data indicate a significant association of: a) confluent IL size with 4th quartile of Erythrocyte Sedimentation Rate (ESR) (OR = 5.250; 95% CI, 1.002 to 27.514) and an independent correlation with sex; b) confluent IL size with 3rd quartile of fibrinogen (OR = 5.5; 95% CI, 1.027 to 29.451); c) confluent IL size with 3rd quartile of platelets (OR= 0.059; 95% CI, 0.003 to 1.175) and independent correlation with sex; d) smaller IL size (OR = 5.25; 95% CI, 1.351 to 20.396) with 3rd quartile of albumin levels and nodular and parenchimal IL size with 2nd (OR = 0.227; 95% CI, 0.053 to 0.981), 3rd (OR = 0.164; 95% CI, 0.038 to 0.711) and 4th (OR = 0.205; 95% CI, 0.048 to 0.870) quartiles albumin levels; e) smaller IL size with 3rd quartile triglycerides (TG) levels (OR = 9; 95% CI, 2.487 to 32.567) and an independent correlation with anterior location. Smaller IL size, anterior AIS turned out to be independently correlated with high serum albumin levels. Finally, high INR and PTT values were associated with worse NIHSS clinical outcomes in contrast to that observed with higher albumin level.

Conclusions

We provide evidence of routine biomarkers levels correlation with acute IL size, independently of age and sex. In addition, we highlight the importance of differentiation of biomarkers normal interval levels for further improvement not only of the clinical decision making but also in post-acute clinical outcome management.

Improving neuro-oncological patients care: basic and practical concepts for nurse specialist in neuro-rehabilitation

Background

Neuro-oncological population well expresses the complexity of neurological disability due to the multiple neurological deficits that affect these patients. Moreover, due to the therapeutical opportunities survival times for patients with brain tumor have increased and more of these patients require rehabilitation care. The figure of nurse in the interdisciplinary specialty of neurorehabilitation is not clearly defined, even if their role in this setting is recognized as being critical and is expanding.

The purpose of the study is to identify the standard competencies for neurorehabilitation nurses that could be taught by means of a specialization course.

Methods

A literature review was conducted with preference given to works published between January 2000 and December 2008 in English. The search strategy identified 523 non-duplicated references of which 271 titles were considered relevant. After reviewing the abstracts, 147 papers were selected and made available to a group of healthcare professionals who were requested to classify them in few conceptual main areas defining the relative topics.

Results

The following five main areas were identified: clinical aspects of nursing; nursing techniques; nursing methodology; relational and organisational models; legal aspects of nursing. The relative topics were included within each area. As educational method a structured course based on lectures and practical sessions was designed. Also multi-choices questions were developed in order to evaluate the participants’ level of knowledge, while a semi-structured interview was prepared to investigate students’ satisfaction.

Conclusions

Literature shows that the development of rehabilitation depends on the improvement of scientific and practical knowledge of health care professionals. This structured training course could be incorporated into undergraduate nursing education programmes and also be inserted into continuing education programmes for graduate nurses. Developing expertise in neuro-rehabilitation for nurses, will be critical to improve overall care and care management of patients with highly complex disabilities as patients affected by brain tumors. The next step will be to start discussing, at the level of scientific societies linked to the field of neurorehabilitation and oncology, the development of a specialisation course in neurorehabilitation nursing.

Equilibrium during static and dynamic tasks in blind subjects: no evidence of cross-modal plasticity

Can visual information be replaced by other sensory information in the control of static and dynamic equilibrium? We investigated the balancing behaviour of acquired and congenitally blind subjects (25 severe visually impaired subjects--15 males and 10 females, mean age 36 +/- 13.5 SD) and age and gender-matched normal subjects under static and dynamic conditions. During quiet stance, the centre of foot pressure displacement was recorded and body sway analysed. Under dynamic conditions, subjects rode a platform continuously moving in the antero-posterior direction, with eyes open (EO) and closed (EC). Balance was inferred by the movement of markers fixed on malleolus, hip and head. Amplitude of oscillation and cross-correlation between body segment movements were computed. During stance, in normal subjects body sway was larger EC than EO. In blind subjects, sway was similar under both visual conditions, in turn similar to normal subjects EC. Under dynamic conditions, in normal subjects head and hip were partially stabilized in space EO but translated as much as the platform EC. In blind subjects head and hip displacements were similar in the EO and the EC condition; with respect to normal subjects EC, body displacement was significantly larger with a stronger coupling between segments. Under both static and dynamic conditions, acquired and congenitally blind subjects had a similar behaviour. We conclude that long-term absence of visual information cannot be substituted by other sensory inputs. These results are at variance with the notion of compensatory cross-modal plasticity in blind subjects and strengthen the hypothesis that vision plays an obligatory role in the processing and integration of other sensory inputs for the selection of the balancing strategy in the control of equilibrium.

Stance- and Locomotion-Dependent Processing of Vibration-Induced Proprioceptive Inflow From Multiple Muscles in Humans

We performed a whole-body mapping study of the effect of unilateral muscle vibration, eliciting spindle Ia firing, on the control of standing and walking in humans. During quiet stance, vibration applied to various muscles of the trunk-neck system and of the lower limb elicited a significant tilt in whole body postural orientation. The direction of vibration-induced postural tilt was consistent with a response compensatory for the illusory lengthening of the stimulated muscles. During walking, trunk-neck muscle vibration induced ample deviations of the locomotor trajectory toward the side opposite to the stimulation site. In contrast, no significant modifications of the locomotor trajectory could be detected when vibrating various muscles of the lower as well as upper limb. The absence of correlation between the effects of muscle vibration during walking and standing dismisses the possibility that vibration-induced postural changes can account for the observed deviations of the locomotor trajectory during walking. We conclude that the dissimilar effects of trunk-neck and lower limb muscle vibration during walking and standing reflect a general sensory-motor plan, whereby muscle Ia input is processed according to both the performed task and the body segment from which the sensory inflow arises.

Time to reconfigure balancing behaviour in man: changing visual condition while riding a continuously moving platform

While balancing on a continuously antero-posterior (A-P) translating platform (10 cm, 0.5 Hz), the head normally oscillates with the platform without vision but is stabilized in space with vision. We estimated the time to shift from one to the other balancing behaviour when visual condition changed at some stage during the balancing trials. Ten subjects performed randomly 50 balancing trials (each lasting 18 s): 10 trials with eyes open (EO), 10 with eyes closed (EC), 15 in which participants started with EO and closed their eyes (condition EO-->EC) in response to an acoustic signal delivered during the trial, and 15 starting with EC and closing their eyes (EC-->EO) in response to the same signal. No other specific instruction was given. Displacements of malleolus, hip and head, and EMG from leg and axial muscles were recorded. Indexes of amplitude of A-P head and hip oscillation and of amplitude of EMG activity were computed. All variables were larger with EC than EO. On changing visual condition during the trial, the pattern of head and hip movement and of muscle activity turned into that appropriate for the new visual condition in a time-interval ranging from about 1 to 2.5 s. For each subject, the mean latency of the change in the balancing behaviour was assessed by statistical methods. On average, the latencies of kinematics and EMG changes proved to be longer for the EO-->EC condition than vice versa. Further, the latencies of the changes were also measured across all EO-->EC and EC-->EO individual trials. These values were clustered around particular epochs of the first few oscillation cycles following the shift in visual condition. The results show that subjects can rapidly adapt their balancing behaviour to the new visual condition. However, they appear to refrain from releasing the new behaviour were this unfit, and unfastened it at appropriate time in the next platform translation cycle. These findings reveal the temporal and spatial features of the automatic release of the new balancing strategy in response to a shift in the ongoing sensory set, and emphasize the swiftness in the change in balancing behaviour when subjects pass from a non-visual to a visual reference frame.

Trunk muscle proprioceptive input assists steering of locomotion

During locomotion, human subjects navigate in their environment and choose the direction by means of the internal representation of space that is continuously updated by sensory input. Aim of this study was to assess whether trunk proprioceptive information plays a role in the definition of the reference frame for orientation. Unilateral trunk muscle vibration was applied during locomotion along a straight path in seven subjects. Vibration was administered either from the onset or in the middle of a seven-step task, under eyes-open (EO) or blindfolded condition. The deviation of the walking trajectory was quantified by the distance of the seventh from the first foot print along the medio-lateral axis. Foot angles and stride lengths were computed for all foot-falls. Vibration produced a clear-cut deviation from the straight-ahead direction when delivered in the middle of blindfolded locomotion. With EO the deviation was much smaller. A mild deviation was obtained in blindfolded condition when vibration started at the onset of locomotion. All deviations from the straight-ahead were accompanied by coherent changes in foot orientation on the ground. Trunk proprioception plays a major role in the definition of locomotor trajectory. Trunk input seems to be weighted against vision and whole-body kinematic information.