AI-Powered Artificial Vision for Visual Prostheses
试验速览
- 阶段
- 不适用
- 状态
- Enrolling By Invitation
- 入组人数
- 7
- 试验地点
- 4
- 主要终点
- Phosphene shape
研究概览
简要总结
Visual impairment is one of the ten most prevalent causes of disability and poses extraordinary challenges to individuals in our society that relies heavily on sight. Living with acquired blindness not only lowers the quality of life of these individuals, but also strains society's limited resources for assistance, care and rehabilitation. However, to date, there is no effective treatment for man patients who are visually handicapped as a result of degeneration or damage to the inner layers of the retina, the optic nerve or the visual pathways. Therefore, there are compelling reasons to pursue the development of a cortical visual prosthesis capable of restoring some useful sight in these profoundly blind patients.
However, the quality of current prosthetic vision is still rudimentary. A major outstanding challenge is translating electrode stimulation into a code that the brain can understand. Interactions between the device electronics and the retinal neurophysiology lead to distortions that can severely limit the quality of the generated visual experience. Rather than aiming to one day restore natural vision (which may remain elusive until the neural code of vision is fully understood), one might be better off thinking about how to create practical and useful artificial vision now.
The goal of this work is to address fundamental questions that will allow the development of a Smart Bionic Eye, a device that relies on AI-powered scene understanding to augment the visual scene (similar to the Microsoft HoloLens), tailored to specific real-world tasks that are known to diminish the quality of life of people who are blind (e.g., face recognition, outdoor navigation, reading, self-care).
详细描述
The investigators will perform basic experimental studies involving humans (BESH) designed to quantify the perceptual experiences of visual prosthesis patients. These experiments will follow standard procedures for collecting behavioral data, and involve simple perceptual tasks (e.g., signal detection, object recognition) and behavioral tasks (e.g., walking towards a goal location).
The investigators will produce visual percepts in visual prosthesis patients either by directly stimulating electrodes (using standard, safe pulse trains), or by asking them to view a computer or projector screen and using standard stimulation protocols (as is standardly used for their devices) to convert the computer or projector screen image into pulse trains on their electrodes. Informed by psychophysical data and computational models, the investigators will test the ability of different stimulus encoding methods to support simple perceptual and behavioral tasks (e.g., object recognition, navigation). These encoding methods may include computer vision methods to e.g. highlight important objects in the scene or machine learning to tailor stimuli to each individual patient. Performance of prosthesis patients will be compared both across stimulus encoding methods and to performance in normally sighted control subjects viewing stimuli manipulated to match the expected perceptual experience of prosthesis patients.
The normal method of stimulation is a chain from a camera mounted on eye glasses through a video processing unit (VPU) which converts the video image into electronic pulse trains. Sometimes the investigators will test subjects using the camera. More often, the investigators will carry out 'direct stimulation' when using an external computer to directly specify pulse trains (e.g., a 300 Hz pulse train with 400 us pulse duration). These direct pulse trains are then sent to the VPU. This VPU contains software that makes sure that these pulse trains are within FDA-approved safety limits. For example, these pulses must be charge-balanced (equal anodic/cathodic charge) and must have a charge density below 35 microCoulombs/cm2. Sometimes the investigators will test subjects using the camera. Sometimes the investigators will directly send pulses to the VPU by directly specifying pulse trains (e.g., send a 1 s 10 Hz cathodic pulse train, with a current amplitude of 100 microAmps and a pulse width of 45 microAmps to Electrode 12 of an Argus II implant).
Important parameters for safety include a) pulses must be charge-balanced (an anodic pulse must be followed quickly by a cathodic pulse and vice versa or the electrode will dissolve), b) charge density should be limited. The frequency of the pulse train and the current amplitude of the pulse train is not actually a critical safety issue, since the electronic/neural interface is robust to extremely high rates of stimulation and high current levels. However, high frequency pulse trains or high amplitude pulse trains can produce discomfort in patients (analogous to going from a dark movie theatre to sunlight) due to inducing large-scale neuronal firing. The investigators will normally be focusing on pulse-train frequencies/amplitudes that are in the normal range used by the patient when using their device. If the investigators use parameters that might be expected to produce a more intense neural response (and therefore have the potential to cause discomfort), they will always introduce them in a step-wise function (e.g. gradually increasing amplitude) while checking that the sensation is not 'uncomfortably bright', and the investigators will immediately decrease the intensity of stimulation if patients report that the sensation approaches discomfort. The PI has experience in this approach and will train all personnel on these protocols.
In response to the stimulation/image on the monitor, subjects will be asked to either make a perceptual judgment or perform a simple behavioral task. Examples include detecting a stimulus ('did you see a light on that trial'), reporting size by drawing on a touch screen, or walking to a target location. Both patient response and reaction time will be recorded.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Basic Science
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Criteria for inclusion of visual prosthesis users:
- •Subject must be at least 18 years of age;
- •Subject has been implanted with a visual prosthesis (e.g., Argus II, Orion, Cortivis)
- •Subject has healed from surgery and the surgeon has cleared the subject for programming;
- •Subject has the cognitive and communication ability to participate in the study (i.e., follow spoken directions, perform tests, and give feedback);
- •Subject is willing to conduct psychophysics testing up to 4-6 hours per day of testing on 3-5 consecutive days;
- •Subject is capable of understanding patient information materials and giving written informed consent;
- •Subject is able to walk unassisted.
- •Criteria for inclusion of sighted control subjects:
- •Subject speaks English;
- •Subject must be at least 18 years of age;
- •Subject has visual acuity of 20/40 or better (corrected);
- •Subject has the cognitive and communication ability to participate in the study (i.e., follow spoken directions, perform tests, and give feedback);
- •Subject is capable of understanding participant information materials and giving written informed consent.
- •Subject is able to walk unassisted
排除标准
- •Visual prosthesis users: Subject is unwilling or unable to travel to testing facility for at least 3 days of testing within a one-week timeframe;
- •Sighted controls: Subject has a history of motion sickness or flicker vertigo
- •All: Subject has language or hearing impairment
研究组 & 干预措施
Perception resulting from AI-powered artificial vision
The investigators will produce visual percepts in visual prosthesis patients either by directly stimulating electrodes (using FDA-approved pulse trains), or by asking them to view a computer or projector screen and using standard stimulation protocols (as is standardly used for their devices) to convert the computer or projector screen image into pulse trains on their electrodes. Informed by psychophysical data and computational models, the investigators will test the ability of different stimulus encoding methods to support simple perceptual and behavioral tasks (e.g., object recognition, navigation). These encoding methods may include computer vision and machine learning methods to highlight important objects in the scene or to highlight nearby obstacles and may be tailored to each individual patient.
干预措施: Visual prosthesis (Device)
结局指标
主要结局
Phosphene shape
时间窗: through study completion, an average of 1 year
The effect of stimulation strategy on the shape of phosphenes elicited by electrical stimulation. Phosphene shape will be recorded via participant drawings on a touchscreen and quantified using image moments (e.g., area, orientation, eccentricity).
Pattern discrimination accuracy
时间窗: through study completion, an average of 1 year
The effect of stimulation strategy on the ability to discriminate patterns (accuracy, precision, recall) elicited by electrical stimulation as assessed by verbal responses
Scene understanding performance
时间窗: through study completion, an average of 1 year
The effect of stimulation strategy to locate objects of interest (accuracy, precision, recall) and relay accurate descriptions of the visual scene as assessed by verbal responses
次要结局
未报告次要终点
