Novel Solution for Using Neural Networks for Kidney Boundary Extraction in 2D Ultrasound Data.

: Kidney ultrasound (US) imaging is a significant imaging modality for evaluating kidney health and is essential for diagnosis, treatment, surgical intervention planning, and follow-up assessments. Kidney US image segmentation consists of extracting useful objects or regions from the total image, which helps determine tissue organization and improve diagnosis. Thus, obtaining accurate kidney segmentation data is an important first step for precisely diagnosing kidney diseases.

Comparative effects of kinect-based versus therapist-based constraint-induced movement therapy on motor control and daily motor function in children with unilateral cerebral palsy: a randomized control trial.

Background: Constraint-induced movement therapy (CIMT) is a prominent neurorehabilitation approach for improving affected upper extremity motor function in children with unilateral cerebral palsy (UCP). However, the restraint of the less-affected upper extremity and intensive training protocol during CIMT may decrease children's motivation and increase the therapist's workload and family's burden. A kinect-based CIMT program, aiming to mitigate the concerns of CIMT, has been developed.

A Music Playback Algorithm Based on Residual-Inception Blocks for Music Emotion Classification and Physiological Information.

Music can generate a positive effect in runners' performance and motivation. However, the practical implementation of music intervention during exercise is mostly absent from the literature. Therefore, this paper designs a playback sequence system for joggers by considering music emotion and physiological signals.

An Ultra-Low Power Surface EMG Sensor for Wearable Biometric and Medical Applications.

In recent years, the surface electromyography (EMG) signal has received a lot of attention. EMG signals are used to analyze muscle activity or to evaluate a patient's muscle status. However, commercial surface EMG systems are expensive and have high power consumption.

Development and Feasibility of a Kinect-Based Constraint-Induced Therapy Program in the Home Setting for Children With Unilateral Cerebral Palsy.

Cerebral palsy (CP) is the leading cause of childhood-onset physical disability. Children with CP often have impaired upper limb (UL) function. Constraint-induced therapy (CIT) is one of the most effective UL interventions for children with unilateral CP.

Environmental Noise Classification with Inception-Dense Blocks for Hearing Aids.

Hearing aids are increasingly essential for people with hearing loss. For this purpose, environmental noise estimation and classification are some of the required technologies. However, some noise classifiers utilize multiple audio features, which cause intense computation.

Continual Learning Strategy in One-Stage Object Detection Framework Based on Experience Replay for Autonomous Driving Vehicle.

Object detection is an important aspect for autonomous driving vehicles (ADV), which may comprise of a machine learning model that detects a range of classes. As the deployment of ADV widens globally, the variety of objects to be detected may increase beyond the designated range of classes. Continual learning for object detection essentially ensure a robust adaptation of a model to detect additional classes on the fly.

Optimizing the Sensor Placement for Foot Plantar Center of Pressure without Prior Knowledge Using Deep Reinforcement Learning.

We study the foot plantar sensor placement by a deep reinforcement learning algorithm without using any prior knowledge of the foot anatomical area. To apply a reinforcement learning algorithm, we propose a sensor placement environment and reward system that aims to optimize fitting the center of pressure (COP) trajectory during the self-selected speed running task. In this environment, the agent considers placing eight sensors within a 7 × 20 grid coordinate system, and then the final pattern becomes the result of sensor placement.

Depth-based dynamic lightness adjustment power-saving algorithm for AMOLED in head-mounted display.

Most of the head-mounted displays take the active-matrix organic light emitting diode (AMOLED) as the primary display panel because of its displaying superiorities. Yet, the AMOLED displays are still regarded as power-hungry components; in order to reduce the power consumption of AMOLED displays, the input image would be suppressed based on the proposed dynamic lightness adjustment algorithm that incorporates the depth information from the stereoscopic images which indicates the saliency, and the lightness of image pixel-wisely. The experiments reveal that the proposed method could achieve the approximately high power-saving rate with lower computational overheads compared to the existing methods.

An Effective Occipitomental View Enhancement Based on Adaptive Morphological Texture Analysis.

This paper aims to present an algorithm that specifically enhances maxillary sinuses using a novel contrast enhancement technique based on the adaptive morphological texture analysis for occipitomental view radiographs. First, the skull X-ray (SXR) is decomposed into rotational blocks (RBs). Second, each RB is rotated into various directions and processed using morphological kernels to obtain the dark and bright features.