Body Movements Research Articles

The validation of inertial measurement units in upper limb movement during wheelchair activity

Introduction: 3D motion capture is accepted to be the gold standard approach to all data collection for the production of accurate data, however, in recent literature the ecological validity of 3D systems has come into question. This has brought about the use of Inertial measurement units (IMU’s) and the investigation into their accuracy in enabling accurate real life scenario data collection. The depth of research on IMU’s in wheelchair data collection is limited, and at current there is limited attempts at a validation in comparison to an established data collection software. This research aims to validate basic upper body motions seen within wheelchair propulsion in an attempt to identify the current limitations of IMU’s. Methods: numerous IMU placements and calibration stances were investigated for the collection of elbow flexion and shoulder flexion. IMU’s for elbow flexion were placed at the wrist and central on the forearm. For shoulder flexion the IMU was placed 1 cm above the elbow joint. During the calibration phase, standing anatomical position with thumbs forwards, palms outwards, bent elbow and straight arms outwards at 90° for elbow and shoulder flexion, respectively. For both shoulder and elbow flexion, the participant started at a neutral position and moved through to 90° of flexion and returned to starting position. Quintic was used as the validated software. Results: the wrist placed IMU determined elbow flexion more accurately than the forearm placed IMU. Range of motion for both shoulder and elbow flexion were well calculated within several degrees when using the anatomical thumbs forwards calibration pose; with 99.97 and 89.69°, respectively compared to 88.48 and 97.32°. However, the degree of elbow flexion was overestimated with a difference of 27.78°, with the IMU being 91.11° and quintic being 63.33°. Similar results were also seen for the prediction of elbow flexion during the starting phase with a difference of 26.58°. Discussion: with range of motion accurately calculated in comparison to quintic, and shoulder flexion maximum and minimum values also being similar when segment angle was calculated. Then the differences are likely due to error in the calculation of joint angle using a calculation of global coordinate system from the IMU coordinate system during data processing. Therefore, future research should target alternate approaches to data processing in order to reduce the errors seen.

Model of Active Solids: Rigid Body Motion and Shape-Changing Mechanisms.

Active solids such as cell collectives, colloidal clusters, and active metamaterials exhibit diverse collective phenomena, ranging from rigid body motion to shape-changing mechanisms. The nonlinear dynamics of such active materials remains, however, poorly understood when they host zero-energy deformation modes and when noise is present. Here, we show that stress propagation in a model of active solids induces the spontaneous actuation of multiple soft floppy modes, even without exciting vibrational modes. By introducing an adiabatic approximation, we map the dynamics onto an effective Landau free energy, predicting mode selection and the onset of collective dynamics. These results open new ways to study and design living and robotic materials with multiple modes of locomotion and shape change.

Flexible staircase triboelectric nanogenerator for motion monitoring and gesture recognition

Triboelectric sensors, which are used in human-computer interaction and condition monitoring, have attracted tremendous scientific interest owing to their broad applicability, high energy utilization, and high accuracy detection. Here, a staircase-style flexible triboelectric sensor assembled by the antimony-doped tin oxide (ATO) functionalized flexible polyvinylidene fluoride polymer (PVDF) composite film is first proposed for gesture recognition and human motion detection. The modified composite film ATO/PVDF with high polarization and large permittivity improves the electrical output of the triboelectric nanogenerator (TENG). Compared with the pure PVDF, the modified PVDF film-based TENG could substantially enhance power density by 11.5 times. The peak voltage and power density of the flexible staircase-style TENG achieve 70 V and 0.58 W/m2, respectively. The flexible triboelectric sensor can be attached to the finger or wrist to obtain movement information through positive/negative signals. A set of rules between gestures and corresponding letters and numbers is defined and a gesture recognition system using deep learning algorithms is developed. The flexible triboelectric sensor realizes human body part bending, gesture, and motion state recognition, offering potential solutions and novel possibilities in smart sensing and human-computer interaction.

ED50 of ciprofol combined with sufentanil for fiberoptic bronchoscopy of different patient populations with pulmonary tuberculosis

BackgroundCiprofol is a promising sedative. This study aims to explore the median effective dose (ED50) of ciprofol in inhibiting responses to fiberoptic bronchoscopy in patients with pulmonary tuberculosis (PTB) of different genders and ages when combined with 0.15 μg/kg sufentanil, and to evaluate its efficacy and safety, providing a reference for the rational use of ciprofol in clinical practice.MethodsPTB patients who underwent bronchoscopy examination and treatment at The Third People’s Hospital of Changzhou between May 2023 and June 2023 were selected and divided into four groups using a stratified random method. All patients received intravenous injection of 0.15 μg/kg sufentanil followed by injection of the test dose of ciprofol according to Dixon’s up-and-down method. The initial dose of ciprofol in all four groups was 0.4 mg/kg, with an adjacent ratio of 1:1.1. The next patient received a 10% increase in the dose of ciprofol if the previous patient in the same group experienced positive reactions such as choking cough, frowning, and body movements during the endoscopy. Otherwise, it was judged as a negative reaction, and the next patient received a 10% decrease in the dose of ciprofol. The transition from a positive reaction to a negative reaction was defined as a turning point, and the study of the group was terminated when seven turning points occurred. Hemodynamic parameters, oxygen saturation and adverse reactions were recorded at different time points in all groups. The Probit regression analysis method was used to calculate the ED50 of ciprofol in the four groups and compare between the groups.ResultsThe ED50 of ciprofol combined with 0.15 μg/kg sufentanil for bronchoscopy in the four groups were 0.465 mg/kg, 0.433 mg/kg, 0.420 mg/kg and 0.396 mg/kg, respectively.ConclusionThe ED50 of ciprofol used for fiberoptic bronchoscopy varied among PTB patients of different genders and ages.Trial registrationThe Chinese Clinical Trial Registry, ChiCTR2300071508, Registered on 17 May 2023.

An embodied perspective on an augmented reality game in school: pupil's bodily experience toward learning

There has long been an increased focus on and investment in digital technology in schools to improve the quality of education. While digital tools have gained access to pedagogical spheres, physical activity has been overlooked, as pupils often engage in activities that require minimal bodily movement. In this article, we discuss pupils’ experiences with learning through an augmented reality (AR)-based game application and explain how the application supports embodied learning. Digital tools, including gaming, can supplement traditional activities, motivate children to become physically active and enhance their learning experiences. Integrating technology and physical activity can create a more varied, meaningful, and dynamic school day, positively supporting pupils’ learning processes. The AR game associated with this study facilitated physical activity and learning experiences through a mobile device application. The empirical material for the study includes interviews with pupils participating in an AR game in mathematics. The findings show that participating in an AR game promoted embodied learning and positively impacted pupils’ motivation, engagement and learning processes. More specifically, AR facilitated learners’ engagement in the learning process by fostering their active involvement through physical and social collaboration and by enhancing the pupils’ joy of learning. Additionally, the pupils expressed that they enjoyed the application’s variations and the experiences that followed working collaboratively with the tasks. Moreover, they commonly found the physical and collaborative components of the AR game exciting and academically motivating. Studies on AR games and technology focusing on the opportunities and pedagogical foundations for their use in education are relevant in these precarious times. Indeed, more knowledge is needed on the ways creative and flexible learning processes that transpire within a technological learning environment influence embodied learning, knowledge that is essential for designing teaching and learning in the technical future.

Machine Learning Approaches for Dementia Detection Through Speech and Gait Analysis: A Systematic Literature Review.

Dementia is a general term for several progressive neurodegenerative disorders including Alzheimer's disease. Timely and accurate detection is crucial for early intervention. Advancements in artificial intelligence present significant potential for using machine learning to aid in early detection. Summarize the state-of-the-art machine learning-based approaches for dementia prediction, focusing on non-invasive methods, as the burden on the patients is lower. Specifically, the analysis of gait and speech performance can offer insights into cognitive health through clinically cost-effective screening methods. A systematic literature review was conducted following the PRISMA protocol (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The search was performed on three electronic databases (Scopus, Web of Science, and PubMed) to identify the relevant studies published between 2017 to 2022. A total of 40 papers were selected for review. The most common machine learning methods employed were support vector machine followed by deep learning. Studies suggested the use of multimodal approaches as they can provide comprehensive and better prediction performance. Deep learning application in gait studies is still in the early stages as few studies have applied it. Moreover, including features of whole body movement contribute to better classification accuracy. Regarding speech studies, the combination of different parameters (acoustic, linguistic, cognitive testing) produced better results. The review highlights the potential of machine learning, particularly non-invasive approaches, in the early prediction of dementia. The comparable prediction accuracies of manual and automatic speech analysis indicate an imminent fully automated approach for dementia detection.

A machine learning based method for tracking of simultaneously imaged neural activity and body posture of freely moving maggot

To understand neural basis of animal behavior, it is necessary to monitor neural activity and behavior in freely moving animal before building relationship between them. Here we use light sheet fluorescence microscope (LSFM) combined with microfluidic chip to simultaneously capture neural activity and body movement in small freely behaving Drosophila larva. We develop a transfer learning based method to simultaneously track the continuously changing body posture and activity of neurons that move together using a sub-region tracking network with a precise landmark estimation network for the inference of target landmark trajectory. Based on the tracking of each labelled neuron, the activity of the neuron indicated by fluorescent intensity is calculated. For each video, annotation of only 20 frames in a video is sufficient to yield human-level accuracy for all other frames. The validity of this method is further confirmed by reproducing the activity pattern of PMSIs (period-positive median segmental interneurons) and larval movement as previously reported. Using this method, we disclosed the correlation between larval movement and left-right asymmetry in activity of a group of unidentified neurons labelled by R52H01-Gal4 and further confirmed the roles of these neurons in bilateral balance of body contraction during larval crawling by genetic inhibition of these neurons. Our method provides a new tool for accurate extraction of neural activities and movement of freely behaving small-size transparent animals.

Stretchable MXene/Carbon Nanotube Bilayer Strain Sensors with Tunable Sensitivity and Working Ranges.

Stretchable strain sensors have gained increasing popularity as wearable devices to convert mechanical deformation of the human body into electrical signals. Two-dimensional transition metal carbides (Ti3C2Tx MXene) are promising candidates to achieve excellent sensitivity. However, MXene films have been limited in operating strain ranges due to rapid crack propagation during stretching. In this regard, this study reports MXene/carbon nanotube bilayer films with tunable sensitivity and working ranges. The device is fabricated using a scalable process involving spray deposition of well-dispersed nanomaterial inks. The bilayer sensor's high sensitivity is attributed to the cracks that form in the MXene film, while the compliant carbon nanotube layer extends the working range by maintaining conductive pathways. Moreover, the response of the sensor is easily controlled by tuning the MXene loading, achieving a gauge factor of 9039 within 15% strain at 1.92 mg/cm2 and a gauge factor of 1443 within 108% strain at 0.55 mg/cm2. These tailored properties can precisely match the operation requirements during the wearable application, providing accurate monitoring of various body movements and physiological activities. Additionally, a smart glove with multiple integrated strain sensors is demonstrated as a human-machine interface for the real-time recognition of hand gestures based on a machine-learning algorithm. The design strategy presented here provides a convenient avenue to modulate strain sensors for targeted applications.

A Machine Learning Model for Predicting Sleep and Wakefulness Based on Accelerometry, Skin Temperature and Contextual Information.

Body-worn accelerometers are commonly used to estimate sleep duration in population-based studies. However, since accelerometry-based sleep/wake-scoring relies on detecting body movements, the prediction of sleep duration remains a challenge. The aim was to develop and evaluate the performance of a machine learning (ML) model to predict accelerometry-based sleep duration and to explore if this prediction can be improved by adding skin temperature data, circadian rhythm based on the estimated midpoint of sleep, and cyclic time features to the model. Twenty-nine adults (17 females), mean (SD) age 40.2 (15.0) years (range 17-70) participated in the study. Overnight polysomnography (PSG) was recorded in a sleep laboratory or at home along with body movement by two accelerometers with an embedded skin temperature sensor (AX3, Axivity, UK) positioned at the low back and thigh. The PSG scoring of sleep/wake was used as ground truth for training the ML model. Based on pure accelerometer data input to the ML model, the specificity and sensitivity for predicting sleep/wake was 0.52 (SD 0.24) and 0.95 (SD 0.03), respectively. Adding skin temperature data and contextual information to the ML model improved the specificity to 0.72 (SD 0.20), while sensitivity remained unchanged at 0.95 (SD 0.05). Correspondingly, sleep overestimation was reduced from 54 min (228 min, limits of agreement range [LoAR]) to 19 min (154 min LoAR). An ML model can predict sleep/wake periods with excellent sensitivity and moderate specificity based on a dual-accelerometer set-up when adding skin temperature data and contextual information to the model.

Hierarchical looping results in extreme extensibility of silk fibre composites produced by Southern house spiders (Kukulcania hibernalis).

Spider silk is a tough and versatile biological material combining high tensile strength and extensibility through nanocomposite structure and its nonlinear elastic behaviour. Notably, spiders rarely use single silk fibres in isolation, but instead process them into more complex composites, such as silk fibre bundles, sheets and anchorages, involving a combination of spinneret, leg and body movements. While the material properties of single silk fibres have been extensively studied, the mechanical properties of silk composites and meta-structures are poorly understood and exhibit a hereto largely untapped potential for the bio-inspired design of novel fabrics with outstanding mechanical properties. In this study, we report on the tensile mechanics of the adhesive capture threads of the Southern house spider (Kukulcania hibernalis), which exhibit extreme extensibility, surpassing that of the viscid capture threads of orb weavers by up to tenfold. By combining high-resolution mechanical testing, microscopy and in silico experiments based on a hierarchical modified version of the Fibre Bundle Model, we demonstrate that extreme extensibility is based on a hierarchical loops-on-loops structure combining linear and coiled elements. The stepwise unravelling of the loops leads to the repeated fracture of the connected linear fibres, delaying terminal failure and enhancing energy absorption. This principle could be used to achieve tailored fabrics and materials that are able to sustain high deformation without failure.

Medium access control protocol based on time division multiple access scheme for wireless body area network

In recent years, the demand for wireless body area network (WBAN) technology has increased, driven by advancements in medical and healthcare applications. WBAN consists of small, low-power, and heterogeneous sensor devices attached inside or outside the body for continuous health monitoring. Medium access control (MAC) is pivotal in addressing WBAN challenges by ensuring reliability and energy efficiency under a dynamic environment caused by body movement. Therefore, to tackle these challenges, this paper presents a MAC protocol based on time division multiple access (TDMA) to enhance the WBAN performance. The proposed TDMA-MAC protocol employs a one-periodic scheduled-based access method to provide reliable data transmission while satisfying the WBAN requirements. The proposed protocol is compared to the IEEE 802.15.6 MAC, enhanced packet scheduling algorithm MAC (EPSA-MAC), and concurrent MAC (C-MAC) protocols based on the performance metrics of packet delivery ratio (PDR), network throughput, energy consumption, and average delay. The simulation results show that the TDMA-MAC protocol outperforms its competitors as it could achieve up to 98% PDR, 30% enhanced throughput, 30% energy optimization, and 20% improvement in average delay.

Leveraging machine learning techniques for student’s attention detection: a review

With the advances of the internet and today's innovation, it has become conceivable to conduct teaching and learning activities remotely through the online platform. Existing research says that student’s attention state and learning result are strongly correlated. However, despite its importance, this can be a challenging task, as students in general taking an online class may be in a variety of different environments and may be multitasking or distracted by other factors. This review paper aims to address these challenges by exploring the opportunities offered by machine learning techniques in attention detection for effective online teaching and learning. By leveraging machine learning algorithms, which can analyze large volumes of data, including eye-tracking, facial expressions, and body movements, we can develop robust models for attention detection in online learning environments. This paper reviews the challenges specific to online learning, such as students' attention deficits and learning styles, and highlights the limitations of current attention detection methods. Furthermore, it provides recommendations to advance attention detection technology, emphasizing the potential of machine learning to enhance attention detection technology for effective online teaching and learning.

Jalan Tendem Menurunkan Resiko Jatuh Lansia

Abstract Background: The aging process causes elderly people to experience functional changes. Some of these changes include neurological, sensory, musculoskeletal and cognitive changes. Some of these problems will have an impact on the elderly's ability to control their balance. One of the most influential factors in reducing the ability to control balance is the musculoskeletal system. Changes in the musculoskeletal system will reduce muscle mass and muscle strength. Decreased muscle mass results in slowness in movement, short footsteps, decreased muscle strength, especially in the lower extremities which experience balance problems and ultimately risk falling. Muscle weakness results in physical decline which is one of the main factors at risk of falls in the elderly. Tandem walking balance training is an exercise in posture or body position, controlling balance, muscle coordination and body movements as well as knowing the risk of falls that elderly people in Tohudan Wetan Village have. Objectives: This study aims to determine the effect of tandem walking balance training on the risk of falls in the elderly in Tohudan Wetan Village, Colomadu, Karanganyar. Methods: The design of this research is quantitative pre-experimental using a one-group pretest-posttest design. Sample selection used purposive sampling technique. Hypothesis testing using Paired Samples T Test. Result: The research results obtained a sig value. 0.000 (p<0.005) means that there is a significant influence on the risk of falls in the elderly before and after being given the tandem walking balance training intervention. Conclusion: This research shows that there is an effect of tandem walking balance training on the risk of falls in the elderly in Tohudan Wetan Village, Colomadu, Karanganyar. Key words: Tandem walking balance training, risk of falls, elderly

Biomechanical Consequences of Walking With the Suspended Backpacks.

This article aimed to investigate the biomechanical mechanisms underlying the energetic advantages of the suspended backpacks during load carriage. In this study, we examined eight adults walking with a 15 kg load at 5 km/h with a designed suspended backpack, in which the load could be switched to locked and suspended with four combinations of stiffness. Mechanical work and metabolic cost were measured during load carriage. The results showed that the suspended backpacks led to an average reduction of 23.35% in positive work, 24.77% in negative work, and a 12.51% decrease in metabolic cost across all suspended load conditions. Notably, the decreased mechanical work predominantly occurred during single support (averaging 84.19% and 71.16% for positive and negative work, respectively), rather than during double support. Walking with the suspended backpack induced a phase shift between body movement and load movement, altering the human-load interaction. This adjustment caused the body and load to move against each other, resulting in flatter trajectories of the human-load system center of mass (COM) velocities and corresponding profiles in ground reaction forces (GRFs), along with reduced vertical excursions of the trunk. Consequently, this interplay led to flatter trajectories in mechanical work rate and reduced mechanical work, ultimately contributing to the observed reduction in energetic expenditure. Understanding these mechanisms is essential for the development of more effective load-carrying devices and strategies in various applications, particularly for enhancing walking abilities during load carriage.

Depersonalization, Meditation, and the Experience of (No-)Self

This paper aims to contribute to an integrated understanding of what goes missing in adverse meditation experiences and in cases of depersonalization disorder. Depersonalization disorder is characterized by distressing alterations in, and sometimes the complete disappearance of, the 'I'-sense. This paper examines the nature of the 'I'-sense and what it means to lose it from a Buddhist perspective. We argue for a nihilist position that the loss of the sense of self arises from misidentifications of the psychophysical complex with non-self elements, such as memories, thoughts, or body movements. Drawing from meditation experiences and depersonalization symptoms, we propose that the sense of self is not a static entity given in experience but fluctuates between various senses of self (and no-self) depending on circumstances. This pluralistic understanding of the various senses of self offers a more nuanced understanding of symptoms in depersonalization disorder and adverse effects of meditation practices.

GENETIC SYNTHESIS OF HYBRID ELECTRO-MECHANICAL SYSTEMS FOR MOTOR-SPINDLE UNITS WITH ADAPTIVE SPATIAL STRUCTURE

The results of fundamental research carried out at the Department of Electromechanics of KPI named after Igor Sikorsky, it was established that the structural organization and evolution of arbitrary classes of technical systems that function on the principles of electromechanical energy conversion is determined by the principles and laws of genetically organized systems. Motor-spindles (M-Ш) also belong to the category of such systems. The energy and genetic core of technical systems with electromechanical energy converters is the active zone of the energy converter, which is a physical and information carrier of genetic information and the corresponding genetic code. The trend of creating multi-coordinate motor-spindle units with a spatially adaptive structure, designed to function as part of metalworking centers and machines with digital control systems, is analyzed. In genetically organized systems, the processes of structuring objects of any level of complexity are implemented on the basis of the elemental information base of genetic programs using genetic synthesis operators. From the point of view of the theory of genetic structure formation, spatial adaptation is the result of chromosomal transformations using the principles of hybridization, mutation, replication, and isomerism. The problem of synthesizing a hybrid multifunctional EM structure for motor-spindle units with a spatially adaptive modular structure was formulated and solved. A generalized genetic model of chromosomal synthesis of hybrid electromechanical modules of motor-spindle units according to a given function has been developed. The structural formulas of hybrid electromagnetic chromosomes, which determine the population structure of original technical solutions, have been determined. Based on the simulation results, the structures of spatially adaptive motor-spindle units with two-, three-, and four-coordinate movement of the working body were synthesized. Based on the results of the research, a genetic catalog was created, which serves as a system basis for the development of original technical solutions for motor-spindle units.

Gait ataxia in alcohol use disorder: A systematic review.

A severe and long-term alcohol use can have adverse effects on lower limb function. Over time, some individuals may develop gait ataxia, which refers to the impairment of controlled lower body movements that are important for walking and maintaining proper gait. Gait ataxia is well-documented in patients who have been diagnosed with alcohol-related Wernicke-Korsakoff syndrome (WKS); however, less is known on how common ataxia is among patients with alcohol use disorder (AUD) without WKS. To date, no study has systematically reviewed the evidence focusing on patients suffering only from AUD. Our aim was to perform a qualitative synthesis of the existing literature examining behavioral signs of gait ataxia among abstinent patients with AUD. Two facets were created encompassing keywords for "alcohol use disorder" and "measures of gait ataxia." Databases, including EMBASE, APA PsycInfo, Medline, and Cochrane Library, were searched for studies, and a quality assessment was performed. Ten studies were identified (37 ≥ ns ≤ 247), which were all rated as being of moderate (N = 7) to good quality (N = 3). The age range was 31.4-53.4 years (weighted mean age: 53.6 years), and 78.3% of the participants were male. Eight studies found that patients with AUD and without WKS exhibited behavioral signs of gait ataxia. Although there is evidence of gait ataxia among patients with AUD, heterogeneous results and methodological shortcomings such as lack of screening for neurocognitive deficits deem these findings preliminary and highlight the need for more research in the future. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Pengaruh Structured Group Exercise Program terhadap Kualitas Hidup Lansia di Paguyuban Lansia RW 08 Kemiri, Kebakkramat, Karanganyar

Abstract Background: The elderly are an age group where every individual experiences health problems, both physical, cognitive and psychosocial. These health problems will cause a decrease in the quality of life in the elderly. Therefore, interventions are needed aimed at minimizing the decline in the quality of life of the elderly. Structured Group Exercise Program (SGEP) is an intervention in the form of planned physical exercise, repetitive and consistent body movements to improve or maintain one or more components of physical fitness. Objectives: This research aims to determine the effect of SGEP on the quality of life of the elderly in the elderly community RW 08 Desa Kemiri, Kecamatan Kebakkramat, Kabupaten Karanganyar. Methods: This research is a quantitative Pre-Experimental Design research with one group pre-post test type. The research was conducted at the elderly community RW 08 Desa Kemiri, Kecamatan Kebakkramat, Kabupaten Karanganyar. The sampling technique used purposive sampling with a total of 27 samples. The research instrument used was the World Health Organization Quality of Life (WHOQOL-BREF). The SGEP intervention was carried out in 8 sessions over 8 weeks. Data analysis used a paired t-test which was processed using SPSS version 25. Results:. The sample for this study was 100% female. Other characteristics were dominated by the elderly age group (59.3%), family status was dominated by the sample living with family (85.2%), and employment was dominated by the non-working sample (59.3%). The results of the paired sample t-test obtained Asmyp Sig. (2-tailed) = 0.000, which means p-value < α (0.05). Conclusion: There is an effect of providing the Structured Group Exercise Program (SGEP) intervention on the quality of life of the elderly in the elderly community RW 08 Desa Kemiri, Kecamatan Kebakkramat, Kabupaten Karanganyar. Keywords: Structured Group Exercise Program, Quality of Life, Elderly

Using high sensitivity DC accelerometers for torque estimation on a wind turbine gearbox

In this paper we propose a novel approach to estimate the torque on a wind turbine gearbox using single-axis high sensitivity DC accelerometers. The torque estimator uses an Augmented Extended Kalman Filter (AEKF), combining physics-based models with measurement data. The accelerometer sensor model is derived by analysing the measurements, leading to the identification of two torque-driven acceleration contributions: acceleration due to force excitation and acceleration due to a change in measurement direction. For the latter, two different sources, with distinct frequency content, are capable of changing the measurement direction. The first source corresponds to rigid body motion (f < 0.15Hz), the second one to ring gear deformation (0.15 < f < 4Hz). Using this information, the measured signal can be filtered to target specific acceleration contributions. The first torque estimation approach targets frequencies from 0.15 to 4Hz and produces a Normalised Mean Absolute Error (NMAE) of 2.12%. The second approach targets frequencies up to 0.15Hz, and will estimate the rigid body deflection angle. The torque is calculated through a linear identified relation between the rigid body angle and applied input torque. This approach yields an NMAE of 2.59%. This leads to the conclusion that high sensitivity DC accelerometers are a valid option for estimating torque on a wind turbine gearbox. These torque monitoring approaches will pave the way for advanced condition monitoring strategies and the calculation of remaining useful lifetime of the gearbox.

Towards seamless conformable and comfortable wearable electronics: Polyimide-supported dry electrodes integrated in knitted fabrics

Wearable electronics contribute directly to advancing numerous biomedical devices in contract with the human body. These electronic devices have been transformed from rigid and bulky into soft and flexible. Conformable electronics is actively pursued in the literature to comply with the curvilinear surface of the skin. To increase the adoption rate, seamless comfortable operation is necessary, which requires more focus on convenient materials such as textiles, compared to elastomer-based technologies. This study demonstrates mechanically reliable stretchable interconnects embedded within textile to achieve both conformability and comfort. Electromyography (EMG) signals provide invaluable information about body motion analysis, muscle nerve and fatigue disorders. Non-invasive surface EMG is the preferred method of measurement since it can be conducted with minimal risk to the subject. In this study, polyimide-supported dry electrodes are integrated in knitted fabrics using a special knit pattern to ensure achieving higher contact surface area with the human skin. The received EMG signals are benchmarked against standard wet electrodes in time and frequency domain, revealing comparable performance. The presented technology exhibits extremely high mechanical reliability, withstanding up to 10,000 cyclic elongations at 60 % strain. The integration strategy is sufficiently strong and durable, retaining its electrical properties after 20 standard washing cycles. The findings indicate that the presented technology holds significant promise towards real-world implementation of seamless, conformable, and comfortable wearable electronics.