A Low-Cost Wearable Device to Estimate Body Temperature Based on Wrist Temperature.

The remote monitoring of vital signs and healthcare provision has become an urgent necessity due to the impact of the COVID-19 pandemic on the world. Blood oxygen level, heart rate, and body temperature data are crucial for managing the disease and ensuring timely medical care. This study proposes a low-cost wearable device employing non-contact sensors to monitor, process, and visualize critical variables, focusing on body temperature measurement as a key health indicator. The wearable device developed offers a non-invasive and continuous method to gather wrist and forehead temperature data. However, since there is a discrepancy between wrist and actual forehead temperature, this study incorporates statistical methods and machine learning to estimate the core forehead temperature from the wrist. This research collects 2130 samples from 30 volunteers, and both the statistical least squares method and machine learning via linear regression are applied to analyze these data. It is observed that all models achieve a significant fit, but the third-degree polynomial model stands out in both approaches. It achieves an R2 value of 0.9769 in the statistical analysis and 0.9791 in machine learning.

Investigating the relationship between pain level and grip and wrist muscles strength in individuals with lateral epicondylitis: is pain a barrier to strength assessment?

PURPOSE: This study was carried out to examine the relationship between rest, activity, and nighttime pain and grip and isokinetic muscle strength of the wrist muscles in individuals with lateral epicondylitis. METHODS: Fifty-six sedentary individuals aged between 18 and 65 years diagnosed with unilateral lateral epicondylitis volunteered to participate in the study. The level of rest, activity, and nighttime pain was evaluated with visual analog scale (VAS). The grip strengths of both arms were evaluated by averaging a maximum of three grip strength measurements using a hand dynamometer. The strength of both wrist flexor and extensor muscles were evaluated with isokinetic dynamometer at angular velocities of 60 and 180°/s with five and 15 concentric repetitions respectively. RESULTS: There was no significant relationship found between the affected side's grip strength and isokinetic muscle strength with rest, activity and nighttime pain (all P > 0.05). However, there was a difference observed between the affected and unaffected side in grip strength and isokinetic strength measurements of all wrist muscles (all P < 0.05); the unaffected side values were found to be higher. CONCLUSION: The result of this study found no correlation between the stated level of pain and the true muscle strength in the affected hand. In line with these findings, we think that assessments involving strength can be made in other musculoskeletal problems where pain is present. However, the findings may not reflect the true muscle strength which will tend to be underrated.

Cumulative Spike Train Estimation for Muscle Excitation Assessment From Surface EMG Using Spatial Spike Detection.

Estimating cumulative spike train (CST) of motor units (MUs) from surface electromyography (sEMG) is essential for the effective control of neural interfaces. However, the limited accuracy of existing estimation methods greatly hinders the further development of neural interface. This paper proposes a simple but effective approach for identifying CST based on spatial spike detection from high-density sEMG. Specifically, we use a spatial sliding window to detect spikes according to the spatial propagation characteristics of the motor unit action potential, focusing on the spikes of activated MUs in a local area rather than those of a specific MU. We validated the effectiveness of our proposed method through an experiment involving wrist flexion/extension and pronation/supination, comparing it with a recognized CST estimation method and an MU decomposition based method. The results demonstrated that the proposed method obtained higher accuracy on multi-DoF wrist torque estimation leveraging the estimated CST compared to the other three methods. On average, the correlation coefficient (R) and the normalized root mean square error (nRMSE) between the estimation results and recorded force were 0.96 ± 0.03 and 10.1% ± 3.7%, respectively. Moreover, there was an extremely high interpretive extent between the CSTs of proposed method and the MU decomposition method. The outcomes reveal the superiority of the proposed method in identifying CSTs and can provide promising driven signals for neural interface.

Wrist Photoplethysmography Signal Quality Assessment for Reliable Heart Rate Estimate and Morphological Analysis.

Photoplethysmographic (PPG) signals are mainly employed for heart rate estimation but are also fascinating candidates in the search for cardiovascular biomarkers. However, their high susceptibility to motion artifacts can lower their morphological quality and, hence, affect the reliability of the extracted information. Low reliability is particularly relevant when signals are recorded in a real-world context, during daily life activities. We aim to develop two classifiers to identify PPG pulses suitable for heart rate estimation (Basic-quality classifier) and morphological analysis (High-quality classifier). We collected wrist PPG data from 31 participants over a 24 h period. We defined four activity ranges based on accelerometer data and randomly selected an equal number of PPG pulses from each range to train and test the classifiers. Independent raters labeled the pulses into three quality levels. Nineteen features, including nine novel features, were extracted from PPG pulses and accelerometer signals. We conducted ten-fold cross-validation on the training set (70%) to optimize hyperparameters of five machine learning algorithms and a neural network, and the remaining 30% was used to test the algorithms. Performances were evaluated using the full features and a reduced set, obtained downstream of feature selection methods. Best performances for both Basic- and High-quality classifiers were achieved using a Support Vector Machine (Acc: 0.96 and 0.97, respectively). Both classifiers outperformed comparable state-of-the-art classifiers. Implementing automatic signal quality assessment methods is essential to improve the reliability of PPG parameters and broaden their applicability in a real-world context.

An electromyographic assessment pilot study on the reliability of the forearm muscles during multi-planar maximum voluntary contraction grip and wrist articulation in young males.

BACKGROUND: Electromyographic systems are widely used in scientific and clinical practice. The reproducibility and reliability of these measures are crucial when conducting scientific research and collecting experimental data. OBJECTIVE: To test the reliability of surface electromyography signals from both the Flexor Digitorum Superficialis (FDS) and Extensor Carpi Radialis Brevis (ECRB) muscles of both the left and right arms during an individual, static multi-planar maximum voluntary contraction handgrip task using the Myon 320 system (Myon AG, Switzerland). METHODS: Eight right-handed male participants performed two maximal handgrip tests in five separate wrist positions using both hands. Muscle activity was recorded from both forearms. Reliability was measured using the Standard Error of Measurement (SEM), Coefficient of Variation (CV) and Intra-class correlation coefficients. Wrist joint position correlations within and between the FDS and ECRB muscle activities were also analysed. RESULTS: Absolute reliability was shown across all positions for both hands with CV and SEM recorded at below 10%. The output measures indicate that the Myon 320 system (Myon AG, Switzerland) produces good to fair reliability when assessing forearm muscle activity. Correlations in the left FDS muscles were negative. Correlations between the left ECRB and left FDS muscles were variable but positive between the right ECRB and right FDS muscles. CONCLUSIONS: The data sets retrieved from all participants were reliably evaluated. Wrist position correlations within and between the FDS and ECRB muscles may have been influenced by hand dominance. The findings demonstrate that the methods and systems outlined in this study can be used reliably in future research.

Cross-sectional assessment of sleep and fatigue in middle-aged Japanese women with primary Sjogren syndrome or rheumatoid arthritis using self-reports and wrist actigraphy.

ABSTRACT: To investigate fatigue, health-related quality of life (HR-QOL), and sleep quality in women with primary Sjogren syndrome (pSS) or rheumatoid arthritis (RA) as compared with healthy controls using self-reports and wrist actigraphy.In this cross-sectional observational study, we evaluated a total of 25 patients (aged 40-75 years) with pSS, 10 with RA, and 17 healthy control subjects living in Japan. The HR-QOL was assessed using the Short Form-36. Fatigue was evaluated using the Short Form-36 vitality score, visual analog scale (VAS) for fatigue, and 2 questionnaire items using scores based on a 4-point Likert scale. Sleep quality was measured using the Japanese version of the Pittsburgh Sleep Quality Index, VAS for sleep quality, and wrist actigraphy for 14 days.Patients with pSS reported severer fatigue and lower HR-QOL than healthy controls, especially in mental health. Based on the Pittsburgh Sleep Quality Index score, 56% of the patients with pSS were poor sleepers, which was higher than healthy controls (29.4%). Furthermore, the patients with pSS scored significantly lower on the VAS for sleep quality than healthy controls (40.5 vs 63.7, P = .001). Although subjective assessments revealed slight sleep disturbances in patients with pSS, wrist actigraphy revealed no differences when compared with healthy controls for total sleep time (421.8 minutes vs 426.5 minutes), sleep efficiency (95.2% vs 96.4%), number of awakenings (1.4 vs 0.9), and wake after sleep onset (22.4 minutes vs 16.1 minutes). Poor subjective sleep quality was associated with enhanced fatigue. However, sleep efficiency, as determined by actigraphy, was not associated with fatigue. Notably, the patients with RA and healthy controls did not differ significantly in terms of fatigue or sleep quality, although patients with RA experienced more nocturnal awakenings than healthy controls (1.7 vs 0.9, P = .04).Patients with pSS experience severe fatigue, poor HR-QOL, and sleep disturbances, which are associated with fatigue. However, wrist actigraphy did not reveal differences in sleep quality, suggesting that it may not be an appropriate measure of sleep in patients with pSS.

Deciphering the constrained total energy expenditure model in humans by associating accelerometer-measured physical activity from wrist and hip.

The constrained total energy expenditure (TEE) model posits that progressive increases in physical activity (PA) lead to increases in TEE; but after certain PA threshold, TEE plateaus. Then, a compensatory reduction in the expenditure of non-essential activities constrains the TEE. We hypothesized that high PA levels as locomotion associate with a compensatory attenuation in arm movements. We included 209 adults (64% females, mean [SD] age 32.1 [15.0] years) and 105 children (40% females, age 10.0 [1.1] years). Subjects wore, simultaneously, one accelerometer in the non-dominant wrist and another in the hip for ≥ 4 days. We analyzed the association between wrist-measured (arm movements plus locomotion) and hip-measured PA (locomotion). We also analyzed how the capacity to dissociate arm movements from locomotion influences total PA. In adults, the association between wrist-measured and hip-measured PA was better described by a quadratic than a linear model (Quadratic-R2 = 0.54 vs. Linear-R2 = 0.52; P = 0.003). Above the 80th percentile of hip-measured PA, wrist-measured PA plateaued. In children, there was no evidence that a quadratic model fitted the association between wrist-measured and hip-measured PA better than a linear model (R2 = 0.58 in both models, P = 0.25). In adults and children, those with the highest capacity to dissociate arm movements from locomotion-i.e. higher arm movements for a given locomotion-reached the highest total PA. We conclude that, in adults, elevated locomotion associates with a compensatory reduction in arm movements (probably non-essential fidgeting) that partially explains the constrained TEE model. Subjects with the lowest arm compensation reach the highest total PA.

Ergonomic assessment of a new hand tool design for laparoscopic surgery based on surgeons' muscular activity.

Laparoscopic surgery techniques are customarily used in non-invasive procedures. That said traditional surgical instruments and devices used by surgeons suffer from certain ergonomic deficiencies that may lead to physical complaints in upper limbs and back and general discomfort that may, in turn, affect the surgeon's skills during surgery. A novel design of the laparoscopic gripper handle is presented and compared with one of the most used instruments in this field in an attempt to overcome this problem. The assessment of the ergonomic feature of the novel design was performed by using time-frequency analysis of the surface electromyography (sEMG) signal during dynamic activities. Singular Spectrum Analysis (SSA) was used to decompose the sEMG signal and extract the median frequency of each muscle to assess muscle fatigue. The results reveal that using the proposed ergonomic grip reduces the mean values of the muscle activity during each of the proposed tasks. The novel design also improves the ease of use in laparoscopic surgery as it minimises high-pressure contact areas, reduces large amplitude movements and promotes a neutral position of the hand, wrist and forearm. Furthermore, the SSA method for time-frequency analysis provides a powerful tool to analyse a prescribed activity in ergonomic terms. The proposed methodology to assess muscle activity during surgery activities may be useful in the selection of surgical instruments when programming extended procedures, as it provides an additional selection criterion based on the surgeon's biomechanics and the proposed activity.

Assessment of the Potential of Wrist-Worn Wearable Sensors for Driver Drowsiness Detection.

Drowsy driving imposes a high safety risk. Current systems often use driving behavior parameters for driver drowsiness detection. The continuous driving automation reduces the availability of these parameters, therefore reducing the scope of such methods. Especially, techniques that include physiological measurements seem to be a promising alternative. However, in a dynamic environment such as driving, only non- or minimal intrusive methods are accepted, and vibrations from the roadbed could lead to degraded sensor technology. This work contributes to driver drowsiness detection with a machine learning approach applied solely to physiological data collected from a non-intrusive retrofittable system in the form of a wrist-worn wearable sensor. To check accuracy and feasibility, results are compared with reference data from a medical-grade ECG device. A user study with 30 participants in a high-fidelity driving simulator was conducted. Several machine learning algorithms for binary classification were applied in user-dependent and independent tests. Results provide evidence that the non-intrusive setting achieves a similar accuracy as compared to the medical-grade device, and high accuracies (>92%) could be achieved, especially in a user-dependent scenario. The proposed approach offers new possibilities for human-machine interaction in a car and especially for driver state monitoring in the field of automated driving.

Automated robot-assisted assessment for wrist active ranges of motion.

The measurement of wrist active range of motion (ROM) is essential for determining the progress of hand functional recovery, which can provide insight into quantitative improvements and enable effective monitoring during hand rehabilitation. Compared with manual methods, which depend on the experience of the therapist, the proposed robot-assisted assessment technique can measure active ROM of human wrists. The robot with a reconfigurable handle design allows for multiple wrist motions. Experiments were conducted with 11 human subjects to measure ROMs of human wrist flexion/extension and radial/ulnar deviation. Reliability analysis was conducted by calculating the intra-class correlation coefficients (ICC), standard error of measurement (SEM) and SEM%. Results showed high reliability (ICC2,1 ≥ 0.89, SEM ≤ 2.36°, SEM% ≤ 6.81%). Future will focus on adaptive joint self-alignment design between human users and robots to further improve its assessment accuracy.

Improved Assessment of Muscle Excitation From Surface Electromyograms in Isometric Muscle Contractions.

We introduce two novel methods for the estimation of muscle excitation from surface electromyograms (EMGs), the so called cumulative motor unit activity index (CAI) and robust CAI (rCAI). Both methods aim to remove the detected motor unit action potential (MUAP) contributions from EMG but do not assess the individual motor unit spike trains. Instead, they directly estimate the cumulative motor unit spike train (CST). We compared the methods with the spatially averaged root-mean-square (RMS) envelope of the EMG signals and with the CST, estimated by the previously introduced convolution kernel compensation (CKC) method. The tests on synthetic EMG with known muscle excitation profiles demonstrated superior accuracy of newly introduced methods. In the case of 64 EMG channels and 20-dB noise, the RMS, CAI, rCAI, and CKC estimators, calculated on 0.125-s-long signal epochs, yielded the normalized RMS error (NRMSE) of 14.5% ± 2.8%, 4.4% ± 3.2%, 4.1% ± 1.8%, and 6.3% ± 4.6%, respectively. In the experimental signals from wrist extensors and flexors, the RMS, CAI, rCAI, and CKC estimations were compared to exerted muscle force. When calculated on 0.125-s-long signal epochs, they yielded the NRMSE of 11.2% ± 3.5%, 8% ± 5.6%, 10.7% ± 6.8%, and 9.0% ± 4.9%, respectively. Therefore, the newly introduced methods exhibit accuracy that is comparable to at least 200-times slower CKC method.

Estimating energy expenditure from wrist and thigh accelerometry in free-living adults: a doubly labelled water study.

BACKGROUND: Many large studies have implemented wrist or thigh accelerometry to capture physical activity, but the accuracy of these measurements to infer activity energy expenditure (AEE) and consequently total energy expenditure (TEE) has not been demonstrated. The purpose of this study was to assess the validity of acceleration intensity at wrist and thigh sites as estimates of AEE and TEE under free-living conditions using a gold-standard criterion. METHODS: Measurements for 193 UK adults (105 men, 88 women, aged 40-66 years, BMI 20.4-36.6 kg m-2) were collected with triaxial accelerometers worn on the dominant wrist, non-dominant wrist and thigh in free-living conditions for 9-14 days. In a subsample (50 men, 50 women) TEE was simultaneously assessed with doubly labelled water (DLW). AEE was estimated from non-dominant wrist using an established estimation model, and novel models were derived for dominant wrist and thigh in the non-DLW subsample. Agreement with both AEE and TEE from DLW was evaluated by mean bias, root mean squared error (RMSE), and Pearson correlation. RESULTS: Mean TEE and AEE derived from DLW were 11.6 (2.3) MJ day-1 and 49.8 (16.3) kJ day-1 kg-1. Dominant and non-dominant wrist acceleration were highly correlated in free-living (r = 0.93), but less so with thigh (r = 0.73 and 0.66, respectively). Estimates of AEE were 48.6 (11.8) kJ day-1 kg-1 from dominant wrist, 48.6 (12.3) from non-dominant wrist, and 46.0 (10.1) from thigh; these agreed strongly with AEE (RMSE ~12.2 kJ day-1 kg-1, r ~ 0.71) with small mean biases at the population level (~6%). Only the thigh estimate was statistically significantly different from the criterion. When combining these AEE estimates with estimated REE, agreement was stronger with the criterion (RMSE ~1.0 MJ day-1, r ~ 0.90). CONCLUSIONS: In UK adults, acceleration measured at either wrist or thigh can be used to estimate population levels of AEE and TEE in free-living conditions with high precision.

Gender, age and socioeconomic variation in 24-hour physical activity by wrist-worn accelerometers: the FinHealth 2017 Survey.

Assessing movement over 24 hours increases our understanding of the total physical activity level and its patterns. In the FinHealth 2017 Survey, a population-based health examination study, 940 participants between 25 and 93 years were instructed to wear an accelerometer (Actigraph GT9X Link) on their non-dominant wrist for 24 hours on 7 consecutive days. Physical activity information was extracted from 100-Hz triaxial 60-second epoch data as average vector magnitude counts per minute (VM cpm). Results were analyzed by gender, 10-year age-groups, employment status, and education. Hourly means were plotted and compared. Analyses included 915 participants (44% men) who wore the device at least 10 hours on 4 or more days, with mean wear time being 149.5 hours (standard deviation of 615.2 minutes).Women had higher average VM cpm than men (p < 0.001), with significant gender differences in all age-groups until 65 years and older. Total physical activity was lower with age, unemployment, and retirement, where the hourly patterns mirrored the findings. Our findings agree with previous large-scale wrist-accelerometry data, but extend current knowledge by providing data on gender and socioeconomic variation in physical activity across 24 hours in a population-based adult sample representing a broad age range.

Actigraphy-measured nocturnal wrist movements and assessment of sleep quality in patients with bullous pemphigoid: a pilot case-control study.

BACKGROUND: Bullous pemphigoid (BP) is a distressing autoimmune bullous disease strongly associated with severe pruritus; however, data concerning pruritus in BP are still scarce. No clinical research evaluating the effect of BP on sleep quality has been conducted. AIM: To evaluate the intensity of pruritus measured by nocturnal wrist movements (NWMs) and the sleep quality in patients with BP using actigraphy in comparison with nonpruritic healthy controls (HCs) with subsequent correlations with an itch visual analogue scale (VAS) as a subjective measure, disease severity [Bullous Pemphigoid Disease Area Index (BPDAI), urticaria/erythema, erosions/blisters] and serum total IgE level. METHODS: In total, 31 patients with newly diagnosed BP (mean ± SD age 75.4 ± 12.3 years) and 40 nonpruritic HCs (age 73.5 ± 11.7 years) were recruited. All participants wore a sleep monitor (ActiSleep+) on the dominant wrist. RESULTS: For patients with BP, median VAS score was 5.5 and median BPDAI was 43 (urticaria/erythema BPDAI was 16, erosions/blisters BPDAI was 29). Scratching, defined as bouts of NWMs, was significantly (P < 0.001) more intensive in patients with BP than in controls. Characteristic of BP was that scratching bouts corresponded with the slowest wrist movements. There were no correlations with VAS, BPDAI or total IgE level. Compared with HCs, patients with BP presented significant (P < 0.001) sleep disturbances, as determined by sleep efficiency, waking after sleep onset and average duration of awakening, and these were strongly correlated with urticaria/erythema BPDAI. CONCLUSION: Nocturnal wrist movements measured by actigraphy are more intensive in patients with BP than in nonpruritic HCs, and characteristically slow movements. Actigraphy method showed very low sleep quality in patients with BP, thus severity of BP has a negative impact on sleep.

Reliability, Construct Validity and Interpretability of the Brazilian version of the Rapid Upper Limb Assessment (RULA) and Strain Index (SI).

BACKGROUND: There are very few observational methods for analysis of biomechanical exposure available in Brazilian-Portuguese. OBJECTIVE: This study aimed to cross-culturally adapt and test the measurement properties of the Rapid Upper Limb Assessment (RULA) and Strain Index (SI). METHODS: The cross-cultural adaptation and measurement properties test were established according to Beaton et al. and COSMIN guidelines, respectively. Several tasks that required static posture and/or repetitive motion of upper limbs were evaluated (n>100). RESULTS: The intra-raters' reliability for the RULA ranged from poor to almost perfect (k: 0.00-0.93), and SI from poor to excellent (ICC2.1: 0.05-0.99). The inter-raters' reliability was very poor for RULA (k: -0.12 to 0.13) and ranged from very poor to moderate for SI (ICC2.1: 0.00-0.53). The agreement was good for RULA (75-100% intra-raters, and 42.24-100% inter-raters) and to SI (EPM: -1.03% to 1.97%; intra-raters, and -0.17% to 1.51% inter-raters). The internal consistency was appropriate for RULA (α=0.88), and low for SI (α=0.65). Moderate construct validity were observed between RULA and SI, in wrist/hand-wrist posture (rho: 0.61) and strength/intensity of exertion (rho: 0.39). CONCLUSION: The adapted versions of the RULA and SI presented semantic and cultural equivalence for the Brazilian Portuguese. The RULA and SI had reliability estimates ranged from very poor to almost perfect. The internal consistency for RULA was better than the SI. The correlation between methods was moderate only of muscle request/movement repetition. Previous training is mandatory to use of observations methods for biomechanical exposure assessment, although it does not guarantee good reproducibility of these measures.

Normative data for the Patient-Rated Wrist Evaluation questionnaire.

STUDY DESIGN: Cross-sectional study. INTRODUCTION: The Patient-Rated Wrist Evaluation (PRWE) questionnaire is used to evaluate functional outcomes after treatment of wrist and hand injuries and nontraumatic conditions. Since patients commonly present with an injury, it is impossible to assess preinjury physical functioning. Therefore, it is important to be aware of the population-based normative data. PURPOSE OF THE STUDY: The aim of this study was to determine the normative data for the PRWE questionnaire. Secondary, we aimed to determine if there were factors influencing these normative data. METHODS: Visitors and employees of 4 hospitals were requested to participate. Excluded were all participants who were scheduled for surgery or were in treatment or after treatment for an injury of the wrist or hand within 1 year after trauma. All participants were asked to complete the PRWE questionnaire and were asked for their age, sex, history of wrist or hand fracture or surgery, daily activities, and the type of employment. The socioeconomic status was determined based on the zip code. RESULTS: The median PRWE score was 0 (interquartile range: 0-8.5) and the mean score 7.7 (standard deviation: 15.0). Women had significantly higher scores compared to men, and younger individuals had significantly lower scores. Participants with a history of wrist or hand fracture or surgery, and participants who were unfit for work had significantly higher scores. Socioeconomic status was not correlated with the PRWE score. DISCUSSION: The purpose was to provide an representative overview of the normative data for the normal population. We did not want to present the data of an unnatural healthy population, which is not representative of the normal population. Deleting patients with chronic wrist or hand complaints, would have resulted in normative values which are not representable for the normal, average population. CONCLUSION: Low scores are observed for the PRWE in the general population. These scores are age and sex dependent and are higher in individuals with a history of wrist or hand fracture or surgery or who are unfit for work.

Robotic assessment of the contribution of motor commands to wrist position sense.

Assessing joint position sense for rehabilitation after neurological injury provides a prognostic factor in recovery and long-term functional outcomes. A common method for testing joint position sense involves the active replication of a joint configuration presented via a passive movement. However, recent evidence showed how this sense is mediated by the centrally generated signals of motor command, such that movements produced volitionally may be coded differently from passive movements and accuracy may be different when matching targets presented actively. To verify this hypothesis we asked ten participants to actively replicate a target wrist angle with the help of a visual feedback in two conditions, which differed in the mode of target presentation: active (aaJPM) or passive (paJPM). The accuracy of target matching, directional bias and variability were analyzed, as well as speed and smoothness of the matching movement and criterion movement in the aaJPM. Overall results indicate higher accuracy and lower variability in the paJPM, while directional bias showed the tendency to overshoot the target regardless of condition. The speed did not differ in the two conditions and movements were smoother in the aaJPM, suggesting a higher confidence by participants in their matching ability. In conclusion, this study suggests that motor commands negatively affect the accuracy of joint position sense when matching involves the integration of visual and proprioceptive information.

Assessment of lower arm movements using one inertial sensor.

Reduction of the number of sensors needed to evaluate arm movements, makes a system for the assessment of human body movements more suitable for clinical practice and daily life assessments. In this study, we propose an algorithm to reconstruct lower arm orientation, velocity and position, based on a sensing system which consists of only one inertial measurement unit (IMU) to the forearm. Lower arm movements were reconstructed using a single IMU and assuming that within a measurement there are moments without arm movements. The proposed algorithm, together with a single IMU attached to the forearm, may be used to evaluate lower arm movements during clinical assessments or functional tasks. In this pilot study, reconstructed quantities were compared with an optical reference system. The limits of agreement in the magnitude of the orientation vector and the norm of the velocity vectors are respectively 4.2 deg (normalized, 5.2 percent) and 7.1 cm/s (normalized, 5.8 percent). The limit of agreement of the difference between the reconstructed positions of both sensing systems were relatively greater 7.7 cm (normalized, 16.8 percent).

Biofeedback Signals for Robotic Rehabilitation: Assessment of Wrist Muscle Activation Patterns in Healthy Humans.

Electrophysiological recordings from human muscles can serve as control signals for robotic rehabilitation devices. Given that many diseases affecting the human sensorimotor system are associated with abnormal patterns of muscle activation, such biofeedback can optimize human-robot interaction and ultimately enhance motor recovery. To understand how mechanical constraints and forces imposed by a robot affect muscle synergies, we mapped the muscle activity of seven major arm muscles in healthy individuals performing goal-directed discrete wrist movements constrained by a wrist robot. We tested six movement directions and four force conditions typically experienced during robotic rehabilitation. We analyzed electromyographic (EMG) signals using a space-by-time decomposition and we identified a set of spatial and temporal modules that compactly described the EMG activity and were robust across subjects. For each trial, coefficients expressing the strength of each combination of modules and representing the underlying muscle recruitment, allowed for a highly reliable decoding of all experimental conditions. The decomposition provides compact representations of the observable muscle activation constrained by a robotic device. Results indicate that a low-dimensional control scheme incorporating EMG biofeedback could be an effective add-on for robotic rehabilitative protocols seeking to improve impaired motor function in humans.

Assessment of the risk and biomechanical consequences of lateral epicondylalgia by estimating wrist and finger muscle capacities in tennis players.

Previous studies suggested that a pronounced weakness of the extensor muscles relative to the flexor muscles could increase the risk of occurrence of lateral epicondylalgia. This study investigates this hypothesis by estimating the ratio of extensor to flexor muscle capacities among healthy non-players (n = 10), healthy tennis players (n = 20), symptomatic players (n = 6), and players who have recovered from lateral epicondylalgia (n = 6). Maximum net joint moments in flexion or extension were measured during seven tasks involving the voluntary contraction of wrist and fingers. Using these data, the muscle capacities of the main muscle groups of the hand (wrist flexors, wrist extensors, finger flexors, finger extensors, and intrinsic muscles) were estimated using a musculoskeletal model. These capacities were then used to compute the extensor/flexor capacity ratios about the wrist and the finger joints. Compared to healthy non-players, healthy players presented higher extensor muscle capacities and greater capacity ratios showing that playing tennis generates specific adaptations of muscle capacities. Interestingly, symptomatic players, similar to those of non-players, showed more imbalanced ratios than healthy players. These results confirm that the ratio of extensor/flexor muscle capacities seems to be associated with lateral epicondylalgia and can be further used to understand its incidence and consequences.