Carbon Conductive Paste Smart Textile Strain Sensor for Sports and Rehabilitation.

Due to the growth observed in the wearable market, stretchable strain sensors have been the focus of several studies. However, combining high sensitivity and linearity with low hysteresis presents a difficult challenge.Here, we propose a stretchable strain sensor obtained with off-the-shelf materials by printing a carbon conductive paste into a piece of fabric to be integrated into a smart garment. This process is cheap and easily scalable, allowing its mass production. The sensor developed has a large sensitivity (GF=11.27), high linearity (R2>0.99), very low hysteresis (γH =4.23%) and brings an added value, for example, in sports or rehabilitation monitoring.

Minding your steps: a cross-sectional pilot study using foot-worn inertial sensors and dual-task gait analysis to assess the cognitive status of older adults with mobility limitations.

BACKGROUND: Cognitive impairment is a critical aspect of our aging society. Yet, it receives inadequate intervention due to delayed or missed detection. Dual-task gait analysis is currently considered a solution to improve the early detection of cognitive impairment in clinical settings. Recently, our group proposed a new approach for the gait analysis resorting to inertial sensors placed on the shoes. This pilot study aimed to investigate the potential of this system to capture and differentiate gait performance in the presence of cognitive impairment based on single- and dual-task gait assessments. METHODS: We analyzed demographic and medical data, cognitive tests scores, physical tests scores, and gait metrics acquired from 29 older adults with mobility limitations. Gait metrics were extracted using the newly developed gait analysis approach and recorded in single- and dual-task conditions. Participants were stratified into two groups based on their Montreal Cognitive Assessment (MoCA) global cognitive scores. Statistical analysis was performed to assess differences between groups, discrimination ability, and association of gait metrics with cognitive performance. RESULTS: The addition of the cognitive task influenced gait performance of both groups, but the effect was higher in the group with cognitive impairment. Multiple dual-task costs, dual-task variability, and dual-task asymmetry metrics presented significant differences between groups. Also, several of these metrics provided acceptable discrimination ability and had a significant association with MoCA scores. The dual-task effect on gait speed explained the highest percentage of the variance in MoCA scores. None of the single-task gait metrics presented significant differences between groups. CONCLUSIONS: Our preliminary results show that the newly developed gait analysis solution based on foot-worn inertial sensors is a pertinent tool to evaluate gait metrics affected by the cognitive status of older adults relying on single- and dual-task gait assessments. Further evaluation with a larger and more diverse group is required to establish system feasibility and reliability in clinical practice. TRIAL REGISTRATION: ClinicalTrials.gov (identifier: NCT04587895).

Using shoe-mounted inertial sensors and stepping exergames to assess the motor-cognitive status of older adults: A correlational study.

Objective: Stepping exergames designed to stimulate physical and cognitive skills can provide important information concerning individuals' performance. In this study, we investigated the potential of stepping and gameplay metrics to assess the motor-cognitive status of older adults. Methods: Stepping and gameplay metrics were recorded in a longitudinal study involving 13 older adults with mobility limitations. Game parameters included games' scores and reaction times. Stepping parameters included length, height, speed, and duration, measured by inertial sensors placed on the shoes while interacting with the exergames. Parameters measured on the first gameplay were correlated against standard cognitive and mobility assessments, including the Montreal Cognitive Assessment (MoCA), gait speed, and the Short Physical Performance Battery. Based on MoCA scores, patients were then stratified into two groups: cognitively impaired and healthy controls. The differences between the two groups were visually inspected, considering their within-game progression over the training period. Results: Stepping and gameplay metrics had moderate-to-strong correlations with cognitive and mobility performance indicators: faster, longer, and higher steps were associated with better mobility scores; better cognitive games' scores and reaction times, and longer and faster steps were associated with better cognitive performance. The preliminary visual analysis revealed that the group with cognitive impairment required more time to advance to the next difficulty level, also presenting slower reaction times and stepping speeds when compared to the healthy control group. Conclusion: Stepping exergames may be useful for assessing the cognitive and motor status of older adults, potentially allowing assessments to be more frequent, affordable, and enjoyable. Further research is required to confirm results in the long term using a larger and more diverse sample.

Detection of Intermittent Claudication from Smartphone Inertial Data in Community Walks Using Machine Learning Classifiers.

Peripheral arterial disease (PAD) causes blockage of the arteries, altering the blood flow to the lower limbs. This blockage can cause the individual with PAD to feel severe pain in the lower limbs. The main contribution of this research is the discovery of a solution that allows the automatic detection of the onset of claudication based on data analysis from patients' smartphones. For the data-collection procedure, 40 patients were asked to walk with a smartphone on a thirty-meter path, back and forth, for six minutes. Each patient conducted the test twice on two different days. Several machine learning models were compared to detect the onset of claudication on two different datasets. The results suggest that we can identify the onset of claudication using inertial sensors with a best case accuracy of 92.25% for the Extreme Gradient Boosting model.

Identity Recognition in Sanitary Facilities Using Invisible Electrocardiography.

This article proposes a new method of identity recognition in sanitary facilities based on electrocardiography (ECG) signals. Our team previously proposed a novel approach of invisible ECG at the thighs using polymeric electrodes, leading to the creation of a proof-of-concept system integrated into a toilet seat. In this work, a biometrics pipeline was devised, which tested four different classifiers, varying the population from 2 to 17 subjects and simulating a residential environment. However, for this approach to be industrially viable, further optimization is required, particularly regarding electrode materials that are compatible with industrial processes. As such, we also explore the use of a conductive silicone material as electrodes, aiming at the industrial-scale production of a toilet seat capable of recording ECG data, without the need for body-worn devices. A desirable aspect when using such a system is matching the recorded data with the monitored user, ideally using a minimal sensor set, further reinforcing the relevance of user identification through ECG signals collected at the thighs. Our approach was evaluated against a reference device for a population of 17 healthy and pathological individuals, covering a wide age range (24-70 years). With the silicone composite, we were able to acquire signals in 100% of the sessions, with a mean heart rate deviation between a reference system and our experimental device of 2.82 ± 1.99 beats per minute (BPM). In terms of ECG waveform morphology, the best cases showed a Pearson correlation coefficient of 0.91 ± 0.06. For biometric detection, the best classifier was the Binary Convolutional Neural Network (BCNN), with an accuracy of 100% for a population of up to four individuals.

A systematic review with meta-analysis of the diagnostic test accuracy of pedicle screw electrical stimulation.

PURPOSE: To provide a systematic review with meta-analysis providing evidence of the current diagnostic test accuracy (DTA) of pedicle screw electrical stimulation. METHODS: A systematic database search on PubMed, Scopus and Web of Science was performed according to the PRISMA-DTA guidelines, and eligibility criteria applied to reduce the results to: (1) only journal articles reporting electrical stimulation of the pedicle screw head, (2) screw position confirmation by imaging techniques, and (3) enough information allowing the calculation of a 2 × 2 contingency table. Sample characteristics, image confirmation method, electrical current threshold and stimulation results were retrieved and analyzed using according to appropriate DTA analysis methods, and allowing the calculation of specificity, sensitivity for pedicle screws insertion at the lumbar and thoracic levels. RESULTS: Lumbar screw stimulation presents a higher sensitivity (0.586 [0.336, 0.798] and specificity (0.984 [0.958, 0.994]) than thoracic screws (sensitivity: 0.270 [0.096; 0.562]; specificity: 0.958 [0.931, 0.975]). The same is observed in terms of the diagnostic odds ratio for lumbar (88.32 [32.136, 242.962]) and thoracic (8.460 [2.139, 33.469]) levels. When performing a sub-group analysis, it is possible to divide the lumbar stimulation threshold as 8 and 10-12 mA, and the thoracic threshold as 6 and 9-12 mA. A threshold of 8 mA at the lumbar level provides higher sensitivity and specificity. Increasing the threshold results in higher specificity but not sensitivity. In fact, at the range of 10-12 mA, the diagnostic validity is too low to confer this technique any robust diagnostic validity. Similarly, at the thoracic level, lower threshold currents are associated with increased sensitivity, but their diagnostic validity is very low. CONCLUSION: Electrical stimulation of the pedicle screw can be used as an adequate diagnostic capability at the lumbar level with a threshold of 8 mA. However, thoracic stimulation is currently not reliable, with very low sensitivity and diagnostic validity at 6 mA or higher.

A Deep Learning Approach for Foot Trajectory Estimation in Gait Analysis Using Inertial Sensors.

Gait performance is an important marker of motor and cognitive decline in older adults. An instrumented gait analysis resorting to inertial sensors allows the complete evaluation of spatiotemporal gait parameters, offering an alternative to laboratory-based assessments. To estimate gait parameters, foot trajectories are typically obtained by integrating acceleration two times. However, to deal with cumulative integration errors, additional error handling strategies are required. In this study, we propose an alternative approach based on a deep recurrent neural network to estimate heel and toe trajectories. We propose a coordinate frame transformation for stride trajectories that eliminates the dependency from previous strides and external inputs. Predicted trajectories are used to estimate an extensive set of spatiotemporal gait parameters. We evaluate the results in a dataset comprising foot-worn inertial sensor data acquired from a group of young adults, using an optical motion capture system as a reference. Heel and toe trajectories are predicted with low errors, in line with reference trajectories. A good agreement is also achieved between the reference and estimated gait parameters, in particular when turning strides are excluded from the analysis. The performance of the method is shown to be robust to imperfect sensor-foot alignment conditions.

Invisible ECG for High Throughput Screening in eSports.

eSports is a rapidly growing industry with increasing investment and large-scale international tournaments offering significant prizes. This has led to an increased focus on individual and team performance with factors such as communication, concentration, and team intelligence identified as important to success. Over a similar period of time, personal physiological monitoring technologies have become commonplace with clinical grade assessment available across a range of parameters that have evidenced utility. The use of physiological data to assess concentration is an area of growing interest in eSports. However, body-worn devices, typically used for physiological data collection, may constitute a distraction and/or discomfort for the subjects. To this end, in this work we devise a novel "invisible" sensing approach, exploring new materials, and proposing a proof-of-concept data collection system in the form of a keyboard armrest and mouse. These enable measurements as an extension of the interaction with the computer. In order to evaluate the proposed approach, measurements were performed using our system and a gold standard device, involving 7 healthy subjects. A particularly advantageous characteristic of our setup is the use of conductive nappa leather, as it preserves the standard look and feel of the keyboard and mouse. According to the results obtained, this approach shows 3-15% signal loss, with a mean difference in heart rate between the reference and experimental device of -1.778 ± 4.654 beats per minute (BPM); in terms of ECG waveform morphology, the best cases show a Pearson correlation coefficient above 0.99.

A Bibliometric Analysis of Intraoperative Neuromonitoring in Spine Surgery.

Intraoperative neuromonitoring (IONM) techniques are usually implemented during spine surgery to avoid nefarious abuse of the nervous system, which can cause postoperative problems. A lack of bibliometric analysis on the topic of IONM in spine surgery has been identified. Therefore, the aims of this study are to provide information about the main contributors to this field and their publication dynamics, as well as conceptual and cooperative networks. Results have shown that a steady publication increase has been occurring since 1991, with high levels of citations in the first decade, but irregular publication rates have been recorded more recently. Research production by country seems to be in line with what is observed in other surgical fields, but research funding for IONM in spine surgery seems to be lower, even with the clear interest of private funding agencies. The conceptual networks have shown the importance of motor-evoked potential, electromyography, and the effect of anesthesia, particularly in scoliosis surgery.

Orientation-Invariant Spatio-Temporal Gait Analysis Using Foot-Worn Inertial Sensors.

Inertial sensors can potentially assist clinical decision making in gait-related disorders. Methods for objective spatio-temporal gait analysis usually assume the careful alignment of the sensors on the body, so that sensor data can be evaluated using the body coordinate system. Some studies infer sensor orientation by exploring the cyclic characteristics of walking. In addition to being unrealistic to assume that the sensor can be aligned perfectly with the body, the robustness of gait analysis with respect to differences in sensor orientation has not yet been investigated-potentially hindering use in clinical settings. To address this gap in the literature, we introduce an orientation-invariant gait analysis approach and propose a method to quantitatively assess robustness to changes in sensor orientation. We validate our results in a group of young adults, using an optical motion capture system as reference. Overall, good agreement between systems is achieved considering an extensive set of gait metrics. Gait speed is evaluated with a relative error of -3.1±9.2 cm/s, but precision improves when turning strides are excluded from the analysis, resulting in a relative error of -3.4±6.9 cm/s. We demonstrate the invariance of our approach by simulating rotations of the sensor on the foot.

Plateau Waves of Intracranial Pressure: Methods for Automatic Detection and Prediction.

Plateau waves are recurrent phenomena observed in traumatic brain injury (TBI) patients, characterised by an increase in intracranial pressure (ICP) above 40 mmHg combined with an almost zero arterial blood pressure (ABP) variation and, hence, a decrease in cerebral perfusion pressure (CPP). A raised ICP for a long period of time, namely plateau waves, can lead to a secondary brain injury. Due to the impaired cerebral autoregulation mechanism these TBI patients present, they are admitted to neurocritical care units (NCCUs) to be under continuous multimodal monitoring, which allows a correct diagnosis for each patient. Plateau waves can end naturally by activating a vasoconstriction mechanism which decreases the amount of blood available in the brain. Alternatively, the phenomenon can end with therapeutic treatment.In this sense, the present study consists in the development of an algorithm capable of automatically detecting plateau waves using offline data, i.e. data already collected from patients. This creates an extra tool which allows for faster detection of events to assist their identification and final diagnosis. Despite the additional steps that can be included to improve the algorithm, the results show good performance, and thus it may be applied in NCCUs.

Comparison of upper limb kinematics in two activities of daily living with different handling requirements.

INTRODUCTION: Recently, kinematic analysis of the drinking task (DRINK) has been recommended to assess the quality of upper limb (UL) movement after stroke, but the accomplishment of this task may become difficult for poststroke patients with hand impairment. Therefore, it is necessary to study ADLs that involve a simpler interaction with a daily life target, such as the turning on a light task (LIGHT). As the knowledge of movement performed by healthy adults becomes essential to assess the quality of movement of poststroke patients, the main goal of this article was to compare the kinematic strategies used by healthy adults in LIGHT with those that are used in DRINK. METHODS: 63 adults, aged 30 to 69 years old, drank water and turned on a light, using both ULs separately, while seated. The movements of both tasks were captured by a 3D motion capture system. End-point and joint kinematics of reaching and returning phases were analysed. A multifactorial analysis of variance with repeated measures was applied to the kinematic metrics, using age, sex, body mass index and dominance as main factors. RESULTS: Mean and peak velocities, index of curvature, shoulder flexion and elbow extension were lower in LIGHT, which suggests that the real hand trajectory was smaller in this task. In LIGHT, reaching was less smooth and returning was smoother than DRINK. The instant of peak velocity was similar in both tasks. There was a minimal anterior trunk displacement in LIGHT, and a greater anterior trunk displacement in DRINK. Age and sex were the main factors which exerted effect on some of the kinematics, especially in LIGHT. CONCLUSION: The different target formats and hand contact in DRINK and LIGHT seem to be responsible for differences in velocity profile, efficiency, smoothness, joint angles and trunk displacement. Results suggest that the real hand trajectory was smaller in LIGHT and that interaction with the switch seems to be less demanding than with the glass. Accordingly, LIGHT could be a good option for the assessment of poststroke patients without grasping ability. Age and sex seem to be the main factors to be considered in future studies for a better match between healthy and poststroke adults.

Co-activation of upper limb muscles during reaching in post-stroke subjects: an analysis of the contralesional and ipsilesional limbs.

The purpose of this study was to analyze the change in antagonist co-activation ratio of upper-limb muscle pairs, during the reaching movement, of both ipsilesional and contralesional limbs of post-stroke subjects. Nine healthy and nine post-stroke subjects were instructed to reach and grasp a target, placed in the sagittal and scapular planes of movement. Surface EMG was recorded from postural control and movement related muscles. Reaching movement was divided in two sub-phases, according to proximal postural control versus movement control demands, during which antagonist co-activation ratios were calculated for the muscle pairs LD/PM, PD/AD, TRIlat/BB and TRIlat/BR. Post-stroke's ipsilesional limb presented lower co-activation in muscles with an important role in postural control (LD/PM), comparing to the healthy subjects during the first sub-phase, when the movement was performed in the sagittal plane (p<0.05). Conversely, the post-stroke's contralesional limb showed in general an increased co-activation ratio in muscles related to movement control, comparing to the healthy subjects. Our findings demonstrate that, in post-stroke subjects, the reaching movement performed with the ipsilesional upper limb seems to show co-activation impairments in muscle pairs associated to postural control, whereas the contralesional upper limb seems to have signs of impairment of muscle pairs related to movement.

Changes in H reflex and V wave following short-term endurance and strength training.

This study examined the effects of 3 wk of either endurance or strength training on plasticity of the neural mechanisms involved in the soleus H reflex and V wave. Twenty-five sedentary healthy subjects were randomized into an endurance group (n = 13) or strength group (n = 12). Evoked V-wave, H-reflex, and M-wave recruitment curves, maximal voluntary contraction (MVC), and time-to-task-failure (isometric contraction at 40% MVC) of the plantar flexors were recorded before and after training. Following strength training, MVC of the plantar flexors increased by 14.4 ± 5.2% in the strength group (P < 0.001), whereas time-to-task-failure was prolonged in the endurance group (22.7 ± 17.1%; P < 0.05). The V wave-to-maximal M wave (V/M(max)) ratio increased significantly (55.1 ± 28.3%; P < 0.001) following strength training, but the maximal H wave-to-maximal M wave (H(max)/M(max)) ratio remained unchanged. Conversely, in the endurance group the V/M(max) ratio was not altered, whereas the H(max)/M(max) ratio increased by 30.8 ± 21.7% (P < 0.05). The endurance training group also displayed a reduction in the H-reflex excitability threshold while the H-reflex amplitude on the ascending limb of the recruitment curve increased. Strength training only elicited a significant decrease in H-reflex excitability threshold, while H-reflex amplitudes over the ascending limb remained unchanged. These observations indicate that the H-reflex pathway is strongly involved in the enhanced endurance resistance that occurs following endurance training. On the contrary, the improvements in MVC following strength training are likely attributed to increased descending drive and/or modulation in afferents other than Ia afferents.

Adjustments in motor unit properties during fatiguing contractions after training.

OBJECTIVE: The objective of the study was to investigate the effect of strength and endurance training on muscle fiber membrane properties and discharge rates of low-threshold motor units of the vasti muscles during fatiguing contractions. METHODS: Twenty-five sedentary healthy men (age (mean ± SD) = 26.3 ± 3.9 yr) were randomly assigned to one of three groups: strength training, endurance training, or a control group. Conventional endurance and strength training was performed 3 d·wk⁻¹, during a period of 6 wk. Motor unit conduction velocity and EMG amplitude of the vastus medialis obliquus and lateralis muscles and biceps femoris were measured during sustained isometric knee extensions at 10% and 30% of the maximum voluntary contraction before and immediately after training. RESULTS: After 6 wk of training, the reduction in motor unit conduction velocity during the sustained contractions at 30% of the maximum voluntary force occurred at slower rates compared with baseline (P < 0.05). However, the rate of decrease was lower after endurance training compared with strength training (P < 0.01). For all groups, motor unit discharge rates declined during the sustained contraction (P < 0.001), and their trend was not altered by training. In addition, the biceps femoris-vasti coactivation ratio declined after the endurance training. CONCLUSIONS: Short-term strength and endurance training induces alterations of the electrophysiological membrane properties of the muscle fiber. In particular, endurance training lowers the rate of decline of motor unit conduction velocity during sustained contractions more than strength training.