Externally validated deep learning model to identify prodromal Parkinson's disease from electrocardiogram
Parkinson’s disease (PD) is a systemic disease that is currently diagnosed when classic motor symptoms become evident. However, pathologic changes in the lower brainstem and peripheral autonomic nervous system likely begin years or decades before symptoms manifest. This study aims to build a generalizable ECG-based fully automatic artificial intelligence (AI) model to predict PD risk during the prodromal stage, up to 5 years before disease diagnosis.
Robotic Tree-fruit harvesting with arrays of Cartesian Arms: A study of fruit pick cycle times
Author links open overlay panelRobotic harvesting can offer a solution to the labor cost and scarcity challenges. This paper uses digitized fruit position data to compute the fruit pick cycle times (PCT) of robotic fruit harvesters with multiple arms arranged in grid configurations. This method can help make design decision that increase the cost-effectiveness of multi-armed robotic harvesters.
A Design Tool To Estimate Maximum Acceptable Manual Arm Forces For Above-Shoulder Work
Above-shoulder work is associated with increased risk for shoulder fatigue and injuries. A new tool is developed that estimates maximum acceptable manual arm forces for work at or above shoulder height. The tool can be used to design acceptable above-shoulder work so that it can be accomplished by most workers.
Hand Posture and Force Estimation Using Surface Electromyography and an Artificial Neural Network
The purpose of this study was to develop an approach to predict hand posture (pinch versus grip) and grasp force using forearm surface electromyography (sEMG) and artificial neural networks (ANNs) during tasks that varied repetition rate and duty cycle. Prior studies have used electromyography with machine learning models to predict grip force but relatively few studies have assessed whether both hand posture and force can be predicted, particularly at varying levels of duty cycle and repetition rate.
