Commercial sleep devices and mobile-phone applications for scoring sleep are gaining ground. In order to provide reliable information about the quantity and/or quality of sleep, their performance needs to be assessed against the current gold-standard, i.e. polysomnography (PSG; measuring brain, eye and muscle activity). We here assessed some commercially available sleep trackers, namely; a commercial activity tracker: Mi band (Xiaomi, BJ, CHN), a scientific actigraph: Motionwatch 8 (CamNTech, CB, UK), and a much used sleep application: Sleep Cycle (Northcube, GOT, SE). We recorded 27 nights in healthy sleepers using PSG and these devices. Surprisingly, all devices had very poor agreement with the gold standard. Sleep parameter comparisons revealed that specifically the Mi band and the sleep cycle application had difficulties in detecting wake periods which negatively affected the total sleep time and sleep efficiency estimations. However, all 3 devices were good in detecting the most basic parameter, the actual time in bed. In summary, our results suggest that, to-date; available sleep trackers do not provide meaningful sleep analysis but may be interesting for simply tracking times in bed. A much closer interaction with the scientific field seems necessary if reliable information shall be derived from such devices in the future.

Manual handling tasks, both in daily activities and at work, require high dexterity and the ability to move objects of different shapes and sizes. However, musculoskeletal disorders that can arise due to aging, disabilities, overloading, or strenuous work can impact the natural capabilities of the hand with serious repercussions both in working and daily activities. To address this, researchers have been developing and proving the benefits of wrist exoskeleton., This paper, which is the part II of a study on wrist exoskeletons, presents and summarizes wearable wrist exoskeleton devices conceived for use in rehabilitation, assistance, and occupational fields. Exoskeletons considered within the study are those available either in a prototyping phase or on the market. They can support the human wrist by relieving pain or mitigating fatigue while allowing at least one movement. According to the requirements to be met, the majority have been designed active (80%) for higher force/torque transmission, and soft for better kinematic compliance, ergonomics, and safety (13 devices out of 24, more than 50%). Electric motors (11 devices out of 24, almost 50%) and cable transmission (9 devices out of 24, almost 40%) are the most common due to their simplicity, controllability, safety, power-to-weight ratio, and the possibility of remote actuation. As sensing technologies, position and force sensors are widely used in all devices (almost 90%). The control strategy depends mainly on the application domain: for rehabilitation, CPM (Control Passive Motion) is preferred (35% of the devices), while for assistance and occupational purposes AAN (Assistance-As-Needed) is more suitable (38% of the devices). What emerges from this analysis is that while rehabilitation and training are fields in which exoskeletons have been grown more easily and gained some user acceptance (almost 18 devices of which 4 are available on the market), relatively few devices have been designed for occupational aims (6 of which only 2 are available on the market) due to difficulties in meeting the acceptance and needs of users. In this perspective, as a result of the state-of-the-art analysis, the authors propose a conceptual idea of a portable soft wrist exoskeleton for occupational assistance.

Wrist-worn fitness trackers and smartwatches are proliferating with an incessant attention towards health tracking. Given the growing popularity of wrist-worn devices across all age groups, a rigorous evaluation for recognizing hallmark measures of physical activities and estimating energy expenditure is needed to compare their accuracy across the lifespan. The goal of the study was to build machine learning models to recognize physical activity type (sedentary, locomotion, and lifestyle) and intensity (low, light, and moderate), identify individual physical activities, and estimate energy expenditure. The primary aim of this study was to build and compare models for different age groups: young [20-50 years], middle (50-70 years], and old (70-89 years]. Participants (n = 253, 62% women, aged 20-89 years old) performed a battery of 33 daily activities in a standardized laboratory setting while wearing a portable metabolic unit to measure energy expenditure that was used to gauge metabolic intensity. Tri-axial accelerometer collected data at 80-100 Hz from the right wrist that was processed for 49 features. Results from random forests algorithm were quite accurate in recognizing physical activity type, the F1-Score range across age groups was: sedentary [0.955 – 0.973], locomotion [0.942 – 0.964], and lifestyle [0.913 – 0.949]. Recognizing physical activity intensity resulted in lower performance, the F1-Score range across age groups was: sedentary [0.919 – 0.947], light [0.813 – 0.828], and moderate [0.846 – 0.875]. The root mean square error range was [0.835 – 1.009] for the estimation of energy expenditure. The F1-Score range for recognizing individual physical activities was [0.263 – 0.784]. Performances were relatively similar and the accelerometer data features were ranked similarly between age groups. In conclusion, data features derived from wrist worn accelerometers lead to high-moderate accuracy estimating physical activity type, intensity and energy expenditure and are robust to potential age-differences.

Understanding the subtle signs of carpal instability and other unique injury patterns in the wrist is a critical skill for radiologists. Proper patient management and outcomes are directly dependent on the accurate interpretation of wrist imaging studies. This review will provide a detailed overview of typical imaging features of carpal trauma and instability, management, and complications, using multimodality imaging and original medical illustrations. A detailed overview of the osseous, ligamentous, arterial anatomy of the wrist, arcs of Gilula, and zones of vulnerability will be provided. Carpal fractures, dislocations, special radiographic views, and imaging pearls will be discussed. Instability patterns and the myriad of associate abbreviations (CID, CIND, CIC, CIA, VISI, DISI, SLD, LTD, MCI, SLAC, SNAC) will be clarified. Expected outcomes, potential complications, and management will be reviewed.

Wrist shape varies greatly across primates and previous studies indicate that the numerous morphological differences among them are related to a complex mixture of phylogeny and function. However, little is known about whether the variation in these various anatomical differences is linked and to what extent the wrist bones vary independently. Here, we used 3D geometric morphometrics on a sample of extant hominids (Homo sapiens, Pan troglodytes, Gorilla gorilla, and Gorilla beringei), to find the model that best describes the covariation patterns among four of the eight carpals (i.e., capitate, lunate, scaphoid, and trapezium). For this purpose, 15 modular hypotheses were tested using the Covariation Coefficient. Results indicate that there is a covariation structure common to all hominids, which corresponds to stronger covariation within each carpal as compared to the covariation between carpals. However, the results also indicate that that there is a degree of codependence in the variation of some carpals, which is unique in humans, chimpanzees, and gorillas, respectively. In humans there is evidence of associated shape changes between the lunate and capitate, and between the scaphoid and trapezium. This covariation between lunate and capitate is also apparent in gorillas, while chimpanzees display the greatest disassociation among carpals, showing low covariation values in all pairwise comparisons. Our analyses indicate that carpals have an important level of variational independence which might suggest a high degree of independent evolvability in the wrists of hominids, and that although weak, the structure of associated changes of these four carpals varies across genera. To our knowledge this is the first report on the patterns of modularity between these four wrist bones in the Homininae and future studies might attempt to investigate whether the anatomical shape associations among carpals are functionally related to locomotion and manipulation.

What drives an individual police officer to activate his body-worn camera (BWC)? Some evidence suggests officer attitudes and resistance to the technology contributes to the equivocal results in studies testing for BWCs effect on use-of-force, complaints, and other outcomes of interest. Leveraging a novel survey and administrative dataset, we investigate the predictors of BWC activation among 147 police officers in a single agency. With a test of three nested models, we find job function covariates offer robust predictive power of how often an officer activates her or his BWC. Neither demographic nor attitudinal measures significantly predict BWC activations, except for a negative relationship with how officers perceive BWC impacts on professional discretion. The study furnishes empirical support for understanding officers as Principled Agents: job function, guided by administrative policy is the most explanatory and parsimonious, while models of attitudes and demographics fail to improve upon the job function model.

Consideration of the individual bone characteristics of the wrist plays a key role in well-functioning biomedical devices and successful surgical procedures. Although geometric differences and individual bone sizes have been analyzed in the literature, detailed morphologic descriptions and correlations covering the entire wrist reported in a clinical context are lacking. This study aimed to perform a comprehensive and automatic analysis of wrist morphology using the freely available “Open Source Carpal Database” (OSCD). We quantified the dimensions of each of the individual carpal bones and their combination. These dimensions were extracted in n=117 datasets of the wrist of the OSCD in anatomical directions and analyzed using descriptive statics and correlation analysis to investigate morphological characteristics under gender-specific aspects. We found that there exist statistical differences between genders, and we concluded that gender specificity is an important variable affecting the utilization of biomedical device designs and clinical treatment.

This study investigated the relationship between wrist flexion and the dynamics of the swing of a croquet mallet. Twenty seven subjects participated in a study which used 3D motion capture equipment and high speed and high-definition video to determine if there is a correlation between the lateral twist of a croquet player’s swing and the flexion of the wrist during that swing. The study found a significant correlation between the amount of flexion of the wrist from the start of the stroke to the top of the backswing and the twist of the mallet head at the top of the backswing (r=0.330, p<0.01). The methodology and findings are relevant to all sports where minimising wrist flexion is favourable for improving consistency of stroke making. Additionally, reducing wrist motion in stroke-making may reduce the incidence of wrist pain and injury in croquet, further supporting recommendations to reduce the amount of wrist flexion during the croquet swing.

Electromyographic (EMG) signals provide information about a person's muscle activity. For hand movements, in particular, the execution of each gesture involves the activation of different combinations of the forearm muscles, which generate distinct electrical patterns. Conversely, the analysis of these muscle activation patterns, represented by EMG signals, allows recognizing which gesture is being performed. In this study, we aimed to implement an automatic identification system of hand or wrist gestures based on supervised Machine Learning (ML) techniques. We trained different computational models and determined which of these showed the best capacity to identify six hand or wrist gestures and generalize between different subjects. We used an open access database containing recordings of EMG signals from 36 subjects. Among the results obtained, we highlight the performance of the Random Forest model, with an accuracy of 95.39%, and the performance of a convolutional neural network with an accuracy of 94.77%.

In this study, an investigation on the influence of In-situ tribo-oxide-layer on non-lubricated tribological behaviours of LM27/SiCp composites was carried out at different applied loads. The variations in wear performance and microstructure of brake lining friction material (LM27) with the addition of different amounts and sizes of SiCp are explored. For this purpose, LM27/SiCp composite materials were manufactured by stir casting route varying the amount of particle reinforced from 3wt.% to 12wt.% with a different size range (fine: 1-20µm and coarse: 106-125µm). Non-lubricated dry wear tests of LM27/SiCp composites samples were trialled at different loads from 9.8N to 49N by using a pin-on-disc machine system. At a contact pressure of 0.2-1 MPa, LM27/SiCp composites with 12wt.% reinforcement showed a lower coefficient of friction than other composites. In-situ formation of oxide layers on the contact region of the specimen supports the self-lubrication during the wear test, which is responsible for better wear performance of LM27/SiCp composites. However, these study portraits that composite with 12wt. % fine size SiCp exhibits better wear performance in comparison to the other developed composites.

This study presents a research plan that utilizes data obtained from wearable devices to identify human activities and gain insights into human behavior. We developed a model capable of classifying activities similar to human behavior and evaluated the effectiveness and generalization capabilities of this model. The data underwent initial preprocessing, including standardization and normalization. Additionally, recognizing the inherent similarities between human activity behaviors, we introduced a multi-layer classifier model. The first layer is a random forest model based on stepwise regression, which may encounter reduced accuracy for similar activities. The second layer employs a Support Vector Machine (SVM) model based on Kernel Fisher Discriminant Analysis (KFDA). KFDA is used to reduce the dimensionality of data points with potential confusion, followed by SVM for classification. The model was experimentally evaluated and applied to four benchmark datasets: UCI DSA, UCI HAR, WISDM, and IM-WSHA. The experimental results demonstrate that our approach achieved recognition accuracies of 99.71%, 98.71%, 99.12%, and 97.6% on these datasets, indicating excellent recognition performance. Furthermore, to assess the model's generalization ability, we performed K-fold cross-validation on the random forest model and utilized ROC curves for the SVM classifier. The results indicate that our multi-layer classifier model exhibits robust generalization capabilities.

A ganglion cyst is a benign fluid-filled sac that typically appears on the dorsal aspect of the wrist, arising idiopathically near the joint capsule or tendon sheath. Diagnosis is primarily clinical, with MRI and ultrasound serving as confirmation tools. Treatment options range from immobilization, aspiration, hydrossection, steroid or hyaluronidase injection, to surgical intervention. Although relatively uncommon, Dorsal Ganglion Cysts (DGC) can lead to Dorsal Wrist Impingement (DWI) syndrome. This syndrome results from the thickening of the wrist capsule due to overuse, injury, or repetitive activities. This thickening can lead to the compression of the extensor carpi radialis brevis (ECRB) tendon during wrist extension and produce tenderness around the lunate. In some refractory cases, MRI findings may show recurrent ganglion cysts, while in others, they may appear "normal." Consequently, the diagnosis remains clinical, and imaging is primarily employed to rule out secondary causes. Management strategies encompass rest, immobilization, occupational therapy, non-steroidal anti-inflammatory drugs (NSAIDs), cortisone injections, and, in certain instances, surgical intervention. Despite the clinical significance of these conditions, limited studies have explored their interrelationship. In this context, we present a rare case involving a 23-year-old female with recurrent DGC accompanied by DWI syndrome. Initially, the patient reported idiopathic left dorsal wrist pain localized around the tendon sheath. Her initial X-ray did not reveal any abnormalities, but MRI identified two ganglion cysts. A series of treatments were initiated, including left tendon sheath hydrossection, corticosteroid injections into the left wrist, and the excision of ganglion cysts from the left wrist. Furthermore, occupational therapy, oral Meloxicam, and Voltaren gel treatments were integrated into the management plan. Subsequent imaging confirmed the resolution of the cysts and an overall enhancement in the range of motion and wrist strength. However, the patient experienced only minimal pain relief, and pain was still elicited during end-range wrist extension and upon dorsal wrist palpation. An electromyography (EMG) test ordered to rule out neuropathic causes did not yield any conclusive results. Nonetheless, a repeat X-ray revealed mild soft tissue swelling on the dorsal side of the wrist, and a follow-up MRI detected ganglion cysts on the dorsal aspect of the lunate and the ECRB tendons. These findings indicated a re-accumulation of dorsal ganglion cysts with a concurrent dorsal impingement syndrome component. Consequently, the patient was referred to an orthopedic surgeon for evaluation and potential revision surgery. This unique case underscores the possibility of developing DWI Syndrome after the removal of a DGC. The diagnosis of this syndrome can be elusive, particularly when X-rays, MRIs, and EMGs yield negative results. Trauma, such as repeated hand surgery or recurrent ganglion cysts, may exacerbate wrist pain despite improvements in range of motion and strength. Special consideration should be given to patients who undergo surgical cyst excisions, as this procedure heightens the risk of recurrence and can irritate the tendon sheath. Collaborative efforts between Physical Medicine and Rehabilitation (PM&amp;R), Occupational Therapy (OT), and surgical teams may play a pivotal role in managing pain associated with these conditions. We propose that future research endeavors should focus on establishing guidelines for the management of this unique condition.

Friction and wear take place on two solid surfaces in sliding contact as a result of the mechanical, thermal and chemical interactions with the participation of environmental species. Electron microscopy and the associated spectroscopic analyses are powerful in probing these mechanisms in spatial resolutions from micro to atomic scale. This article provides a review of the author’s work in the wear and friction mechanisms of PVD hard coatings in which various SEM- and TEM-based microscopic and spectroscopic techniques were employed. Understanding on the failure mechanisms and the origin of self-adaptive friction has been improved to nano-scale. Other related issues are also discussed, such as sample preparation techniques for cross-sectional electron microscopy, energy dispersive X-ray spectroscopy and electron energy loss spectroscopy.