Unlabelled: This study examined the control of standing balance while wearing construction stilts. Motion capture data were collected from nine expert stilt users and nine novices. Three standing conditions were analysed: ground, 60 cm stilts and an elevated platform. Each task was also performed with the head extended as a vestibular perturbation. Both expert and novice groups exhibited lower displacement of the whole body centre of mass and centre of pressure on construction stilts. Differences between the groups were only noted in the elevated condition with no stilts, where the expert group had lower levels of medial-lateral displacement of the centre of pressure. The postural manipulation revealed that the expert group had superior balance to the novice group. Conditions where stilts were worn showed lower levels of correspondence to the inverted pendulum model. Under normal conditions, both expert and novice groups were able to control their balance while wearing construction stilts.
Practitioner Summary: This work investigated the effects of experience on the control of balance while using construction stilts. Under normal conditions, expert and novice stilt users were able to control their balance while wearing construction stilts. Differences between the expert and novice users were revealed when the balance task was made more difficult, with the experts showing superior balance in these situations.
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http://dx.doi.org/10.1080/00140139.2015.1062921 | DOI Listing |
JAMA Cardiol
January 2025
Department of Emergency Medicine, Rush University Medical Center, Chicago, Illinois.
Importance: Lung ultrasound (LUS) aids in the diagnosis of patients with dyspnea, including those with cardiogenic pulmonary edema, but requires technical proficiency for image acquisition. Previous research has demonstrated the effectiveness of artificial intelligence (AI) in guiding novice users to acquire high-quality cardiac ultrasound images, suggesting its potential for broader use in LUS.
Objective: To evaluate the ability of AI to guide acquisition of diagnostic-quality LUS images by trained health care professionals (THCPs).
Langenbecks Arch Surg
January 2025
Department for the Promotion of Medical Device Innovation, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Purpose: Assessing surgical skills is vital for training surgeons, but creating objective, automated evaluation systems is challenging, especially in robotic surgery. Surgical procedures generally involve dissection and exposure (D/E), and their duration and proportion can be used for skill assessment. This study aimed to develop an AI model to acquire D/E parameters in robot-assisted radical prostatectomy (RARP) and verify if these parameters could distinguish between novice and expert surgeons.
View Article and Find Full Text PDFJ Am Coll Surg
January 2025
Department of Surgery, Stanford University, Stanford, CA.
Background: Motion-tracking has been shown to correlate with expert and novice performance but has not been used for skill development. For skill development, performance goals must be defined. We hypothesize that using wearable sensor technology, motion tracking outcomes can be identified in those deemed practice-ready and used as benchmarks for precision learning.
View Article and Find Full Text PDFJ Dent Sci
December 2024
Oral and Maxillofacial Surgery and Digital Implant Surgery Research Unit, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand.
Background/purpose: The increasing importance of computer assisted implant surgery (CAIS) in the practice of implant dentistry calls for adequate education and training of clinicians. However, limited evidence exists to support optimal educational strategies and best practices. This study aimed to investigate the effectiveness of distributed training with dynamic CAIS (d-CAIS) on the precision of freehand implant placement by inexperienced operators.
View Article and Find Full Text PDFClin Teach
February 2025
Department of Surgery, University of Toronto, Toronto, Ontario, Canada.
Purpose: The development of the Diabetic Wound Assessment Learning Tool (DiWALT) has previously been described. However, an examination of its application to a larger, more heterogeneous group of participants is lacking. In order to allow for a more robust assessment of the psychometric properties of the DiWALT, we applied it to a broader group of participants.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!