Enhancing accuracy and convenience of golf swing tracking with a wrist-worn single inertial sensor.

In this study, we address two technical challenges to enhance golf swing trajectory accuracy using a wrist-worn inertial sensor: orientation estimation and drift error mitigation. We extrapolated consistent sensor orientation from specific address-phase signal segments and trained the estimation with a convolutional neural network. We then mitigated drift error by applying a constraint on wrist speed at the address, backswing top, and finish, and ensuring that the wrist's finish displacement aligns with a virtual circle on the 3D swing plane.

Intravascular Papillary Endothelial Hyperplasia in Association with Eccrine Angiokeratomatous Hamartoma.

Eccrine angiokeratomatous hamartoma is a variant of eccrine angiomatous hamartoma. Histopathologically, it shows both features of eccrine angiomatous hamartoma with components of angiokeratoma. Eccrine angiokeratomatous hamartoma is extremely rare.

Preoperative mean platelet volume is a prognostic biomarker for survival in patients with gastric cancer: A cohort study.

This study aimed to evaluate the prognostic potential of mean platelet volume (MPV) in gastric cancer (GC) patients. Patients with stage I-III GC who underwent gastrectomy were enrolled in this study. Cox regression analysis was performed to evaluate the determinants of overall survival (OS) and disease-free survival (DFS).

Effects of Short-term Mobile Application Use on Weight Reduction for Patients with Type 2 Diabetes.

Background: The increasing prevalence of type 2 diabetes mellitus (T2DM) has led to a significant health burden. Technological advancements have highlighted the benefits of digital therapeutics for chronic diseases. In this study, we aimed to investigate the effects of a mobile application on weight reduction in patients with T2DM.

Cutaneous Infection Caused by Skin Coining 'Gua Sha' in Korean Healthy Female.

Nontuberculous mycobacteria are ubiquitous environmental organisms that are rare pathogens in immunocompetent individuals. However, cutaneous nontuberculous mycobacteria infections have been increasingly associated with invasive procedures, including surgery, liposuction, filler injection, intramuscular injection, mesotherapy, piercing, acupuncture, and cupping therapy. Herein, we report the first case of cutaneous nontuberculous mycobacteria infection caused by the East-Asian traditional treatment 'Gua Sha', also known as scraping, coining or spooning in English.

Estimation of the ground reaction forces from a single video camera based on the spring-like center of mass dynamics of human walking.

In clinical studies, the ground reaction forces (GRFs) during walking have found being highly useful. Therefore, the force sensing shoes with small sensors and estimation methods based on kinematics from motion capture systems or inertial measurement units were proposed. Recent studies demonstrated methods of extracting GRFs from whole-body joint kinematics, which requires a significant computational load.

Estimation of Three-Dimensional Lower Limb Kinetics Data during Walking Using Machine Learning from a Single IMU Attached to the Sacrum.

Kinetics data such as ground reaction forces (GRFs) are commonly used as indicators for rehabilitation and sports performance; however, they are difficult to measure with convenient wearable devices. Therefore, researchers have attempted to estimate accurately unmeasured kinetics data with artificial neural networks (ANNs). Because the inputs to an ANN affect its performance, they must be carefully selected.

Spring-loaded inverted pendulum modeling improves neural network estimation of ground reaction forces.

Inertial-measurement-unit (IMU)-based wearable gait-monitoring systems provide kinematic information but kinetic information, such as ground reaction force (GRF) are often needed to assess gait symmetry and joint loading. Recent studies have reported methods for predicting GRFs from IMU measurement data by using artificial neural networks (ANNs). To obtain reliable predictions, the ANN requires a large number of measurement inputs at the cost of wearable convenience.

Golf Swing Segmentation from a Single IMU Using Machine Learning.

Golf swing segmentation with inertial measurement units (IMUs) is an essential process for swing analysis using wearables. However, no attempt has been made to apply machine learning models to estimate and divide golf swing phases. In this study, we proposed and verified two methods using machine learning models to segment the full golf swing into five major phases, including before and after the swing, from every single IMU attached to a body part.

Three Dimensional Upper Limb Joint Kinetics of a Golf Swing with Measured Internal Grip Force.

The biomechanics of a golf swing have been of interest to golfers, instructors, and biomechanists. In addition to the complexity of the three-dimensional (3D) dynamics of multi-segments of body, the closed-chain body posture as a result of both hands holding a club together makes it difficult to fully analyze the 3D kinetics of a golf swing. To identify the hand-grip joint force and torque applied by each hand, we directly measured the 3D internal grip force of nine registered professional golfers using an instrumented grip.

Prediction of Lower Limb Kinetics and Kinematics during Walking by a Single IMU on the Lower Back Using Machine Learning.

Recent studies have reported the application of artificial neural network (ANN) techniques on data of inertial measurement units (IMUs) to predict ground reaction forces (GRFs), which could serve as quantitative indicators of sports performance or rehabilitation. The number of IMUs and their measurement locations are often determined heuristically, and the rationale underlying the selection of these parameter values is not discussed. Using the dynamic relationship between the center of mass (CoM), the GRFs and joint kinetics, we propose the CoM as a single measurement location with which to predict the dynamic data of the lower limbs, using an ANN.

A bipedal compliant walking model generates periodic gait cycles with realistic swing dynamics.

A simple spring mechanics model can capture the dynamics of the center of mass (CoM) during human walking, which is coordinated by multiple joints. This simple spring model, however, only describes the CoM during the stance phase, and the mechanics involved in the bipedality of the human gait are limited. In this study, a bipedal spring walking model was proposed to demonstrate the dynamics of bipedal walking, including swing dynamics followed by the step-to-step transition.

Tinea capitis in adults: A 18-year retrospective, single-centre study in Korea.

Background: Tinea capitis (TC) is a dermatophyte infection involving hair and scalp and occurs primarily in prepubertal children. However, data on adults are limited.

Objectives: The aim of this study was to evaluate epidemiological, clinical and mycological characteristics of TC in adults in Korea.

Estimation of unmeasured ground reaction force data based on the oscillatory characteristics of the center of mass during human walking.

To enhance the wearability of portable motion-monitoring devices, the size and number of sensors are minimized, but at the expense of quality and quantity of data collected. For example, owing to the size and weight of low-frequency force transducers, most currently available wearable gait measurement systems provide only limited, if any, elements of ground reaction force (GRF) data. To obtain the most GRF information possible with a minimal use of sensors, we propose a GRF estimation method based on biomechanical knowledge of human walking.

Kinematics of lower limbs during walking are emulated by springy walking model with a compliantly connected, off-centered curvy foot.

The dynamics of the center of mass (CoM) during walking and running at various gait conditions are well described by the mechanics of a simple passive spring loaded inverted pendulum (SLIP). Due to its simplicity, however, the current form of the SLIP model is limited at providing any further information about multi-segmental lower limbs that generate oscillatory CoM behaviors and their corresponding ground reaction forces. Considering that the dynamics of the CoM are simply achieved by mass-spring mechanics, we wondered whether any of the multi-joint motions could be demonstrated by simple mechanics.

Provision of oral hygiene services as a potential method for preventing periodontal disease and control hypertension and diabetes in a community health centre in Korea.

This study aimed to evaluate the effects of a community-based oral hygiene service on general and periodontal health indicators of patients with hypertension and type 2 diabetes mellitus visiting a community health centre in Korea. The study used a one-group pretest-posttest and interrupted time-series design. A total of 151 participants (45% male), with a mean age of 63 ± 8.

The Development of an IMU Integrated Clothes for Postural Monitoring Using Conductive Yarn and Interconnecting Technology.

Spinal disease is a common yet important condition that occurs because of inappropriate posture. Prevention could be achieved by continuous posture monitoring, but most measurement systems cannot be used in daily life due to factors such as burdensome wires and large sensing modules. To improve upon these weaknesses, we developed comfortable "smart wear" for posture measurement using conductive yarn for circuit patterning and a flexible printed circuit board (FPCB) for interconnections.