Exercise & Fitness

Machine learning approaches for data-driven process monitoring of biological wastewater treatment plant: A review of research works on benchmark simulation model No. 1(BSM1).

In the past decade, machine learning techniques have seen wide industrial applications for design of data-based process monitoring systems with an aim to improve industrial productivity. An efficient process monitoring system for wastewater treatment process (WWTP) ensures increased efficiency and effluents meeting stringent emission norms. Benchmark simulation model No. 1 (BSM1) provides a simula...

Normalization Techniques in Training DNNs: Methodology, Analysis and Application.

Normalization techniques are essential for accelerating the training and improving the generalization of deep neural networks (DNNs), and have successfully been used in various applications. This paper reviews and comments on the past, present and future of normalization methods in the context of DNN training. We provide a unified picture of the main motivation behind different approaches from the...

From Corrective to Predictive Maintenance-A Review of Maintenance Approaches for the Power Industry.

Appropriate maintenance of industrial equipment keeps production systems in good health and ensures the stability of production processes. In specific...

The concepts of muscle activity generation driven by upper limb kinematics.

BACKGROUND: The underlying motivation of this work is to demonstrate that artificial muscle activity of known and unknown motion can be generated base...

Could chatbots help devise the next pandemic virus?

An MIT class exercise suggests AI tools can be used to order a bioweapon, but some are skeptical.

Impact of Obstructive Sleep Apnea Syndrome on Time to Complete Recovery of Continence After Robot-Assisted Radical Prostatectomy: A Propensity Score Matching Analysis.

Postoperative urinary incontinence after robot-assisted radical prostatectomy (RARP) represents a bothersome side effect, which may permanently affec...

Quadrifecta outcomes and their predictors following robotic radical prostatectomy: a study of newly established robotic center in India.

Active surveillance (AS), radical prostatectomy (RP), and radical radiotherapy (RT) are the three options for localized prostate cancer. Only a few st...

Machine learning algorithms for identifying predictive variables of mortality risk following dementia diagnosis: a longitudinal cohort study.

Machine learning (ML) could have advantages over traditional statistical models in identifying risk factors. Using ML algorithms, our objective was to...

First case of robot-assisted radical cystectomy and intracorporeal neobladder reconstruction with the Hugo RAS system: step-by-step surgical setup and technique.

Robotic assisted radical cystectomy (RARC) is a standard option for the treatment of bladder cancer. Currently, novel platforms are entering the marke...

Game-based learning as training to use a chemotherapy preparation robot.

INTRODUCTION: In 2015, our university hospital pharmacy acquired the PharmaHelp robot system to automate part of its chemotherapy production. Complex ...

Barriers and facilitators to physical activity and further digital exercise intervention among inactive British adolescents in secondary schools: a qualitative study with physical education teachers.

BACKGROUND: Previous studies indicated that physical education programs in schools were unsuccessful to ameliorate physical activity (PA) behaviors am...

CNN-LSTM Model for Recognizing Video-Recorded Actions Performed in a Traditional Chinese Exercise.

Identifying human actions from video data is an important problem in the fields of intelligent rehabilitation assessment. Motion feature extraction an...

Knowledge in Motion: A Comprehensive Review of Evidence-Based Human Kinetics.

This comprehensive review examines critical aspects of evidence-based human kinetics, focusing on bridging the gap between scientific evidence and pra...

Robot-assisted partial nephrectomy in morbidly obese patients: a VCQI database study.

To compare perioperative outcomes following robot-assisted partial nephrectomy (RAPN) in patients with morbid obesity (body mass index (BMI > 40 kg/m)...

Counting Activities Using Weakly Labeled Raw Acceleration Data: A Variable-Length Sequence Approach with Deep Learning to Maintain Event Duration Flexibility.

This paper presents a novel approach for counting hand-performed activities using deep learning and inertial measurement units (IMUs). The particular ...

Intentional enterotomies: validation of a novel robotic surgery training exercise.

While laparoscopic simulation-based training is a well-established component of general surgery training, no such requirement or standardized curricul...

Determination of optimum intensity and duration of exercise based on the immune system response using a machine-learning model.

One of the important concerns in the field of exercise immunology is determining the appropriate intensity and duration of exercise to prevent suppres...

Prediction of oxygen uptake kinetics during heavy-intensity cycling exercise by machine learning analysis.

Nonintrusive estimation of oxygen uptake (V̇o) is possible with wearable sensor technology and artificial intelligence. V̇o kinetics have been accurat...

AI-Driven sleep staging from actigraphy and heart rate.

Sleep is an important indicator of a person's health, and its accurate and cost-effective quantification is of great value in healthcare. The gold sta...

Deep learning-based measurement of echocardiographic data and its application in the diagnosis of sudden cardiac death.

This study aimed to evaluate the potential of deep learning applied to the measurement of echocardiographic data in patients with sudden cardiac death...