Emerging Methods to Objectively Assess Pruritus in Atopic Dermatitis.

INTRODUCTION:Atopic dermatitis (AD) is an inflammatory skin disease with a chronic, relapsing course. Clinical features of AD vary by age, duration, and severity but can include papules, vesicles, erythema, exudate, xerosis, scaling, and lichenification. However, the most defining and universal symptom of AD is pruritus. Pruritus or itch, defined as an unpleasant urge to scratch, is problematic for many reasons, particularly its negative impact on quality of life. Despite the profoundly negative impact of pruritus on patients with AD, clinicians and researchers lack standardized and validated methods to objectively measure pruritus. The purpose of this review is to discuss emerging methods to assess pruritus in AD by describing objective patient-centered tools developed or enhanced over the last decade that can be utilized by clinicians and researchers alike. METHODS:This review is based on a literature search in Medline, Embase, and Web of Science databases. The search was performed in February 2019. The keywords were used "pruritus," "itch," "atopic dermatitis," "eczema," "measurements," "tools," "instruments," "accelerometer," "wrist actigraphy," "smartwatch," "transducer," "vibration," "brain mapping," "magnetic resonance imaging," and "positron emission tomography." Only articles written in English were included, and no restrictions were set on study type. To focus on emerging methods, prioritization was given to results from the last decade (2009-2019). RESULTS:The search yielded 49 results in PubMed, 134 results in Embase, and 85 results in Web of Science. Each result was independently reviewed in a standardized manner by two of the authors (M.S., K.L.), and disagreements between reviewers were resolved by consensus. Relevant findings were categorized into the following sections: video surveillance, acoustic surveillance, wrist actigraphy, smart devices, vibration transducers, and neurological imaging. Examples are provided along with descriptions of how each technology works, instances of use in research or clinical practice, and as applicable, reports of validation studies and correlation with other methods. CONCLUSION:The variety of new and improved methods to evaluate pruritus in AD is welcomed by clinicians, researchers, and patients alike. Future directions include next-generation smart devices as well as exploring new territories, such as identifying biomarkers that correlate to itch and machine-learning programs to identify itch processing in the brain. As these efforts continue, it will be essential to remain patient-centered by developing techniques that minimize discomfort, respect privacy, and provide accurate data that can be used to better manage itch in AD

3D Interaction System with Multiple Identified,Small,Wireless,Battery-less,Occlusion-free Magnetic Markers

Tohoku University北村喜

Comparison of wearable measurement systems for estimating trunk postures in manual material handling, A

2017 Fall.Includes bibliographical references.Epidemiologic studies have established that awkward trunk postures during manual materials handling are associated with an increased risk of developing occupational low back disorders. With recent advances in motion capture technology, emerging wearable measurement systems have been designed to quantify trunk postures for exposure assessments. Wearable measurement systems integrate portable microelectromechanical sensors, real-time processing algorithms, and large memory capacity to effectively quantify trunk postures. Wearable measurement systems have been available primarily as research tools, but are now quickly becoming accessible to health and safety professionals for industrial application. Although some of these systems can be highly complex and deter health and safety professionals from using them, other systems can serve as a simpler, more user-friendly alternative. These simple wearable measurement systems are designed to be less intricate, allowing health and safety professionals to be more willing to utilize them in occupational posture assessments. Unfortunately, concerns regarding the comparability and agreement between simple and complex wearable measurement systems for estimating trunk postures are yet to be fully addressed. Furthermore, application of wearable measurement systems has been affected by the lack of adaptability of sensor placement to work around obstructive equipment and bulky gear workers often wear on the job. The aims of the present study were to 1) compare the Bioharness™3, a simple wearable measurement system, to Xsens™, a complex wearable measurement system, for estimating trunk postures during simulated manual material handling tasks and 2) to explore the effects of Xsens sensor placement on assessing trunk postures. Thirty participants wore the two systems simultaneously during simulated tasks in the laboratory that involved reaching, lifting, lowering, and pushing a load for ten minutes. Results indicated that the Bioharness 3 and Xsens systems are comparable for strictly estimating trunk postures that involved flexion and extension of 30° or less. Although limited to a short range of trunk postures, the Bioharness also exhibited moderate to strong agreement and correlations with the Xsens system for measuring key metrics commonly used in exposure assessments, including amplitude probability distribution functions and percent time spent in specific trunk posture categories or bins. The Bioharness is suggested to be an a more intuitive alternative to the Xsens system for posture analysis, but industrial use of the device should be warranted in the context of the exposure assessment goals. In addition, a single motion sensor from the Xsens system placed on the sternum yielded comparable and consistent estimates to a sensor secured on the sternum relative to a motion sensor on the sacrum. Estimates included descriptive measures of trunk flexion and extension and percent time spent in specific trunk posture categories. Using one motion sensor instead of two may serve as an alternative for sensor placement configuration in situations where worker portable equipment or personal preference prevents preferred sensor placement

Objective assessment of movement disabilities using wearable sensors

The research presents a series of comprehensive analyses based on inertial measurements obtained from wearable sensors to quantitatively describe and assess human kinematic performance in certain tasks that are most related to daily life activities. This is not only a direct application of human movement analysis but also very pivotal in assessing the progression of patients undergoing rehabilitation services. Moreover, the detailed analysis will provide clinicians with greater insights to capture movement disorders and unique ataxic features regarding axial abnormalities which are not directly observed by the clinicians

A telerehabilitation system based on wireless motion capture sensors

The constant growth of the elderly population in the world creates new challenges and opportunities in health care systems. New technological solutions have to be found in order to meet the needs and demands of our aging society. The welfare and quality of life of the elderly population must be a priority. Continuous physical activity will play an important role, due to the increase of the retirement age. However, physiotherapy can be expensive, even when the desire movements are autonomous and simple, also requires people to move to rehabilitation centres. Within this context, this paper describes the development and preliminary tests of a wireless sensor network, based on wearable inertial and magnetic sensors, applied to the capture of human motion. This will enable a personalized home-based rehabilitation system for the elderly or people in remote physical locations.Project “AAL4ALL”, co-financed by the European Community Fund FEDER through COMPETE – Programa Operacional Factores de Competitividade (POFC).FCT – Foundation for Science and Technology – Lisbon, Portugal, through project PEst-C/CTM/LA0025/2013

Appl Ergon

The performance of an inertial measurement unit (IMU) system for directly measuring thoracolumbar trunk motion was compared to that of the Lumbar Motion Monitor (LMM). Thirty-six male participants completed a simulated material handling task with both systems deployed simultaneously. Estimates of thoracolumbar trunk motion obtained with the IMU system were processed using five common methods for estimating trunk motion characteristics. Results of measurements obtained from IMUs secured to the sternum and pelvis had smaller root-mean-square differences and mean bias estimates in comparison to results obtained with the LMM than results of measurements obtained solely from a sternum mounted IMU. Fusion of IMU accelerometer measurements with IMU gyroscope and/or magnetometer measurements was observed to increase comparability to the LMM. Results suggest investigators should consider computing thoracolumbar trunk motion as a function of estimates from multiple IMUs using fusion algorithms rather than using a single accelerometer secured to the sternum in field-based studies.T42OH008491/ACL/ACL HHSUnited States/U54OH007548/ACL/ACL HHSUnited States/T42 OH008491/OH/NIOSH CDC HHSUnited States/U54 OH007548/OH/NIOSH CDC HHSUnited States/5U54OH007548-13A/OH/NIOSH CDC HHSUnited States/5T42OH008491-08/OH/NIOSH CDC HHSUnited States

Biosignal‐based human–machine interfaces for assistance and rehabilitation : a survey

As a definition, Human–Machine Interface (HMI) enables a person to interact with a device. Starting from elementary equipment, the recent development of novel techniques and unobtrusive devices for biosignals monitoring paved the way for a new class of HMIs, which take such biosignals as inputs to control various applications. The current survey aims to review the large literature of the last two decades regarding biosignal‐based HMIs for assistance and rehabilitation to outline state‐of‐the‐art and identify emerging technologies and potential future research trends. PubMed and other databases were surveyed by using specific keywords. The found studies were further screened in three levels (title, abstract, full‐text), and eventually, 144 journal papers and 37 conference papers were included. Four macrocategories were considered to classify the different biosignals used for HMI control: biopotential, muscle mechanical motion, body motion, and their combinations (hybrid systems). The HMIs were also classified according to their target application by considering six categories: prosthetic control, robotic control, virtual reality control, gesture recognition, communication, and smart environment control. An ever‐growing number of publications has been observed over the last years. Most of the studies (about 67%) pertain to the assistive field, while 20% relate to rehabilitation and 13% to assistance and rehabilitation. A moderate increase can be observed in studies focusing on robotic control, prosthetic control, and gesture recognition in the last decade. In contrast, studies on the other targets experienced only a small increase. Biopotentials are no longer the leading control signals, and the use of muscle mechanical motion signals has experienced a considerable rise, especially in prosthetic control. Hybrid technologies are promising, as they could lead to higher performances. However, they also increase HMIs’ complex-ity, so their usefulness should be carefully evaluated for the specific application