View clinical trials related to Vision, Low.
Filter by:Background: CLN3 involves vision loss observed around the preschool years, with eventual progression to blindness within 1-3 years. Researchers want to test an assistive device that may help children with CLN3 or blindness. Objective: To learn if it is safe, easy, and useful for children with CLN3 or blindness to use the OrCam. Eligibility: People aged 6-18 years who have either CLN3-related disease or blindness. Design: Participants will be screened with the following: Medical history Physical exam Family history Eye exam and vision tests. They will get eyedrops to dilate their eyes. Psychological and neurocognitive tests. They will be asked questions and observed for how they do various tasks, such as talking, playing, writing, drawing, and solving problems. Hearing tests. They may wear headphones or earplugs. Electrodes may be taped to their head. Blood samples Skin biopsy, if needed Cheek cell, saliva, or urine samples The OrCam is the size of and weighs about half as much as a pack of gum. It is attached to eyeglass frames by magnets. Participants will do tasks before and after they have been trained on the OrCam. They will do these tasks without or with using the OrCam. Participants will be given an OrCam to use for 1 week or 1 month. They will have check-in sessions with the study team. Participants and/or their caregivers will be asked about abilities, behaviors, social skills, learning methods, intelligence, and health-related quality of life. Participants samples may be used for genetic testing and/or to make a type of stem cell. Participation will last for 1-5 weeks.
Approximately 217 million people worldwide currently suffer from low vision, which impacts a broad range of activities of daily living and is associated with depression and increased mortality. Over half of the patients presenting for low vision services have eye disease that affects the fovea and surrounding macula and leads to central vision loss (CVL). People with CVL are forced to use eccentric vision as a substitute for their impaired fovea, however eye movement control and visual function is impaired with eccentric vision. Recent evidence and preliminary results from the investigators show that rehabilitation methods can help improve oculomotor control and this can lead to improved functional outcomes. The investigators have developed new feedback-based training methods that aim to improve eccentric vision use by patients with CVL. In a series of studies, the investigators examine rehabilitation of fixation control, smooth pursuit eye movements that track moving objects and saccadic eye movements that abruptly change the point of regard. The investigators examine how visual feedback, scotoma awareness methods and hand-eye coordination can improve eccentric vision use. Improvements in oculomotor control are quantified with eye tracking methods and associated changes in visual function are quantified with acuity, contrast sensitivity and reading performance. The proposed research therefore develops and translates state-of-the-art methods in basic science to clinical applications. Accomplishing the proposed aims will provide new and improved methods for rehabilitation strategies for visual impairment. The ultimate goal of this proposal is to maximize the residual visual function of people with low vision and to help them to live independently, thereby improving quality of life and minimizing the economic and social burden of visual impairment.
Study is a randomized clinical trial evaluating the efficacy of novel mobile application technologies (including Seeing AI, Aira, and Supervision+) to improve quality of life in older adults with low vision by expanding community access and providing assistance with activities of daily living. Aira provides real-time remote personal assistance through a sighted Aira agent supplying direct feedback to assist with visual tasks. Seeing AI provides optical character recognition allowing any text to be read aloud, color identification, bar code reading, scene description, and facial recognition based on stored photos. Supervision + allows one to use the phone as a magnifier, providing magnification and contrast enhancement using the camera of the mobile phone. This study seeks to understand the potential of these technologies to improve daily activities, community participation, independence, and self-sufficiency in this group by examining a technological approach, which has not yet undergone rigorous investigation in a diverse population of older adults with visual impairment. Project objectives are to evaluate mobile applications in a wide range of visual disability, categorized into three groups: (1) mild to moderate visual acuity loss, (2) severe to profound visual acuity loss, and (3) legal blindness secondary to visual field loss. Participants are randomized to one of three intervention groups: (1) Supervision+ application, (2) Aira application, or (3) Seeing AI application for a period of 6 months. For the Aira intervention group, participants will be assigned either with 'restricted' access (current open access areas plus 30 minutes/month anywhere), or 'unrestricted' access (700 minutes), for a period of 3 months with a 3 month cross-over period. Participants may elect to continue the study for an additional 3 months during which time they have access to all 3 study mobile applications. Outcome measures include assessment of changes at three, six and nine months post-intervention for: visual ability, health state (including depression), self-efficacy, loneliness, life space, distances travelled from the home, and types of services obtained.
According to the WHO's definition of visual impairment, as of 2018, there were approximately 1.3 billion people with visual impairment in the world, and only 10% of countries can provide assisting services for the rehabilitation of visual impairment. Although China is one of the countries that can provide rehabilitation services for patients with visual impairment, due to restrictions on the number of professionals in various regions, uneven diagnosis and treatment, and regional differences in economic conditions, not all visually impaired patients can get the rehabilitation of assisting device fitting. Traditional statistical methods were not enough to solve the problem of intelligent fitting of assisting devices. At present, there are almost no intelligent fitting models of assisting devices in the world. Therefore, in order to allow more low-vision patients to receive accurate and rapid rehabilitation services, we conducted a cross-sectional study on the assisting devices fitting for low-vision patients in Fujian Province, China in the past five years, and at the same time constructed a machine learning model to intelligently predict the adaptation result of the basic assisting devices for low vision patients.
The purpose of the current study was to compare the visual performance after bilateral implantation of the Panoptix IOL , or the AT LISA IOL or Tecnis Symfony IOL . The focus was on intermediate vision, defocus curves, and contrast sensitivity.
According to the WHO's definition of visual impairment, as of 2018, there were approximately 1.3 billion people with visual impairment in the world, and only 10% of countries can provide assisting services for the rehabilitation of visual impairment. Although China is one of the countries that can provide rehabilitation services for patients with visual impairment, due to restrictions on the number of professionals in various regions, uneven diagnosis and treatment, and regional differences in economic conditions, not all visually impaired patients can get the rehabilitation of assisting device fitting. Traditional statistical methods were not enough to solve the problem of intelligent fitting of assisting devices. At present, there are almost no intelligent fitting models of assisting devices in the world. Therefore, in order to allow more low-vision patients to receive accurate and rapid rehabilitation services, we conducted a cross-sectional study on the assisting devices fitting for low-vision patients in Fujian Province, China in the past five years, and at the same time constructed a machine learning model to intelligently predict the adaptation result of the basic assisting devices for low vision patients.
This study is aimed at examining the BCVA from try-on glasses constructed from measurements from the EyeQue VisionCheck.
Primary objective of this study is the development and validation of a web-based application for the examination of the distance visual acuity of normal- and low-vision patients.
Primary objective of our study is the development and validation of an application for smart-TVs for the self-examination of the distant visual acuity of patients diagnosed with macular edema.
The human subject research is a randomized, controlled training trial that tests the effectiveness of three Virtual Reality-based Intelligent Orientation and Mobility Specialists (VR-IOMSs) in teaching orientation and mobility (O&M) task skills to low vision patients. It will be conducted on two sites, University of Alabama at Birmingham (UAB) and Alabama Institute for Deaf and Blind (AIDB). The same protocol will be used on both sites. UAB will be the sIRB for the trial. Three O&M tasks will be studied, timing to cross a signalized street using the near lane parallel traffic surge skill, timing to cross an uncontrolled street using the traffic gap judgment skill and learning outdoor numbering system. A VR-IOMS will be develop for each task. The training does not involve research subjects walking into street traffic. Low vision subjects who have difficulties with these O&M tasks due to their impaired vision will be randomized into three groups, learning the task from a VR-IOMS (experimental group), from a human Certified Orientation & Mobility Specialist (COMS) in real streets (active control group) and not learning the task but spending the same amount of time watching low vision education videos (placebo group). All subjects will be evaluated by COMSs in real streets around the two study sites before training (pre-training), within 3 days after the completion of training (post-training) and 3 months after the completion of training (follow up). Their ability to perform the O&M tasks will be assess quantitatively using objective methods. COMSs who conduct these evaluations will be blinded for subject training assignment. The primary outcome measure is the training effect, the difference in task performance between the pre-training and post-training real street evaluations. The training effects of the 3 groups will be compared to determine the training effectiveness of the VR-IOMS relative to human COMS. Secondary outcome measures include the retainment of the training effect. Objective assessment of the VR-IOMS training process and trainee subjective evaluation of the VR-IOMS training will also be analyzed.