Recent lesion studies have shown that left hemisphere lesions often give rise to frank sign language aphasias in deaf signers, whereas right hemisphere lesions do not, suggesting similar patterns of hemispheric asymmetry for signed and spoken language. We present here a case of a left-handed, deaf, life-long signer who became aphasic after a right-hemisphere lesion. The subject exhibits deficits in sign language comprehension and production typically associated with left hemisphere damaged signers. He also exhibits evidence of local versus global deficits similar to left-hemisphere lesioned hearing patients. This case represents reversed lateralization for sign language and also may represent reversed lateralization for visuo-spatial abilities in a deaf signer.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1080/13554790590944717 | DOI Listing |
Sci Rep
January 2025
University Institute of Computing, Chandigarh University, Punjab, India.
Automatic Sign Language Recognition Systems (ASLR) offers smooth communication between hearing-impaired and normal-hearing individuals, enhancing educational opportunities for impaired. However, it struggles with "curse of dimensionality" due to excessive features resulting in prolonged training time and exhaustive computational demand. This paper proposes technique that integrates machine learning and swarm intelligence to effectively address this issue.
View Article and Find Full Text PDFAfr J Disabil
December 2024
Department of Audiology, Faculty of Human and Community Development, University of the Witwatersrand, Braamfontein, South Africa.
Background: Parents of Deaf or hard-of-hearing (DHH) children are faced with a plethora of overwhelming decisions concerning their children, particularly during the early stages of development. Among these decisions are those concerning assistive devices and the modes of communication for their child.
Objectives: The aim of this study was to explore the perceptions of parents of DHH children towards the various modes of communication for their children within the South African context.
Ann Transl Med
December 2024
Division of Advanced Gastrointestinal and Bariatric Surgery, Mayo Clinic, Jacksonville, FL, USA.
Background: Addressing language barriers through accurate interpretation is crucial for providing quality care and establishing trust. While the ability of artificial intelligence (AI) to translate medical documentation has been studied, its role for patient-provider communication is less explored. This review evaluates AI's effectiveness in clinical translation by assessing accuracy, usability, satisfaction, and feedback on its use.
View Article and Find Full Text PDFJ Periodontol
January 2025
Department of Biomedical and Neuromotor Sciences, School of Dentistry - Division of Periodontology and Implantology, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Background: Crown cementation is a common technique for implant-supported prosthodontics. However, for possible slipping of the cement below the mucosal margin, its thorough removal poses some issues. The objective of this study was to evaluate the presence of submucosal cement residues in patients with peri-implant disease by endoscopic visualization and to investigate the potential correlation between the pathological scenario and the spatial position of cement residues.
View Article and Find Full Text PDFData Brief
February 2025
ADA University, Baku, Azerbaijan.
Advancements in sign language processing technology hinge on the availability of extensive, reliable datasets, comprehensive instructions, and adherence to ethical guidelines. To facilitate progress in gesture recognition and translation systems and to support the Azerbaijani sign language community we present the Azerbaijani Sign Language Dataset (AzSLD). This comprehensive dataset was collected from a diverse group of sign language users, encompassing a range of linguistic parameters.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!