Eye Segmentation Method for Telehealth: Application to the Myasthenia Gravis Physical Examination.

Due to the precautions put in place during the COVID-19 pandemic, utilization of telemedicine has increased quickly for patient care and clinical trials. Unfortunately, teleconsultation is closer to a video conference than a medical consultation, with the current solutions setting the patient and doctor into an evaluation that relies entirely on a two-dimensional view of each other. We are developing a patented telehealth platform that assists with diagnostic testing of ocular manifestations of myasthenia gravis. We present a hybrid algorithm combining deep learning with computer vision to give quantitative metrics of ptosis and ocular muscle fatigue leading to eyelid droop and diplopia. The method works both on a fixed image and frame by frame of the video in real-time, allowing capture of dynamic muscular weakness during the examination. We then use signal processing and filtering to derive robust metrics of ptosis and l ocular misalignment. In our construction, we have prioritized the robustness of the method versus accuracy obtained in controlled conditions in order to provide a method that can operate in standard telehealth conditions. The approach is general and can be applied to many disorders of ocular motility and ptosis.

Boston cognitive assessment (BOCA) - a comprehensive self-administered smartphone- and computer-based at-home test for longitudinal tracking of cognitive performance.

Longitudinal cognitive testing is essential for developing novel preventive interventions for dementia and Alzheimer's disease; however, the few available tools have significant practice effect and depend on an external evaluator. We developed a self-administered 10-min at-home test intended for longitudinal cognitive monitoring, Boston Cognitive Assessment or BOCA. The goal of this project was to validate BOCA. BOCA uses randomly selected non-repeating tasks to minimize practice effects. BOCA evaluates eight cognitive domains: 1) Memory/Immediate Recall, 2) Combinatorial Language Comprehension/Prefrontal Synthesis, 3) Visuospatial Reasoning/Mental rotation, 4) Executive function/Clock Test, 5) Attention, 6) Mental math, 7) Orientation, and 8) Memory/Delayed Recall. BOCA was administered to patients with cognitive impairment (n = 50) and age- and education-matched controls (n = 50). Test scores were significantly different between patients and controls (p < 0.001) suggesting good discriminative ability. The Cronbach's alpha was 0.87 implying good internal consistency. BOCA demonstrated strong correlation with Montreal Cognitive Assessment (MoCA) (R = 0.90, p < 0.001). The study revealed strong (R = 0.94, p < 0.001) test-retest reliability of the total BOCA score one week after participants' initial administration. The practice effect tested by daily BOCA administration over 10 days was insignificant (ß = 0.03, p = 0.68). The effect of the screen size tested by BOCA administration on a large computer screen and re-administration of the BOCA to the same participant on a smartphone was insignificant (ß = 0.82, p = 0.17; positive ß indicates greater score on a smartphone). BOCA has the potential to reduce the cost and improve the quality of longitudinal cognitive tracking essential for testing novel interventions designed to reduce or reverse cognitive aging. BOCA is available online gratis at www.bocatest.org .

A Feasibility Study of AlzLife 40 Hz Sensory Therapy in Patients with MCI and Early AD.

Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) are debilitating diseases that affect millions of individuals and have notoriously limited treatment options. One emerging therapy, non-invasive 40 Hz sensory therapy delivered through light and sound has previously shown promise in improving cognition in Alzheimer Disease (AD) rodent models. Small studies in humans have proven safe and tolerable, however exploration of feasibility and utility is limited. The purpose of this study is to examine the feasibility of this treatment in a human population through a smart tablet application that emits light and sound waves at 40 Hz to the user over the span of 1 h a day. Confirmation of entrainment of 40 Hz stimulation in the cerebral cortex was performed via EEG. 27 preliminary subjects with subjective cognitive complaints, Mild Cognitive Impairment, or AD were enrolled in the study; 11 participants completed 6 months of therapy. Of those that discontinued treatment, other health issues and difficulties with compliance were the most common causes. Participants were followed with Montreal Cognitive Assessment (MOCA) and Boston Cognitive Assessment (BOCA). For participants with subjective cognitive complaints, 2 of the 4 had improved MOCA score and 1 of 4 had improved BOCA score. For the participant with MCI, his MOCA score improved. For AD participants, 2 out of 6 had improved MOCA score and 3 of the 6 stayed stable, while 3 of 6 BOCA score improved. 4 of 11 participants specifically increased their MOCA scores in the Memory Index section. Of the 8 participants/caregivers able to speak to perceived usefulness of the study, 6 spoke to at least some level of benefit. Of these 6, 2 enrolled with subjective cognitive complaint, 1 had MCI, and 3 had AD. The therapy did not have reported side effects. However, those who did not finish the study experienced issues obtaining and operating a smart tablet independently as well as complying with the therapy. Overall, further exploration of this treatment modalities efficacy is warranted.

A Digital Telehealth System to Compute the Myasthenia Gravis Core Examination Metrics.

Background: Telemedicine practice for neurological diseases has grown significantly during the COVID-19 pandemic.Telemedicine offers an opportunity to assess digitalization of examinations and enhances access to modern computer vision and artificial intelligence processing to annotate and quantify examinations in a consistent and reproducible manner. The Myasthenia Gravis Core Examination (MG-CE) has been recommended for the telemedicine evaluation of patients with myasthenia gravis. Objective: We aimed to assess the ability to take accurate and robust measurements during the examination, which would allow improvement in workflow efficiency by making the data acquisition and analytics fully automatic and thereby limit the potential for observation bias. Methods: We used Zoom (Zoom Video Communications) videos of patients with myasthenia gravis undergoing the MG-CE. The core examination tests required 2 broad categories of processing. First, computer vision algorithms were used to analyze videos with a focus on eye or body motions. Second, for the assessment of examinations involving vocalization, a different category of signal processing methods was required. In this way, we provide an algorithm toolbox to assist clinicians with the MG-CE. We used a data set of 6 patients recorded during 2 sessions. Results: Digitalization and control of quality of the core examination are advantageous and let the medical examiner concentrate on the patient instead of managing the logistics of the test. This approach showed the possibility of standardized data acquisition during telehealth sessions and provided real-time feedback on the quality of the metrics the medical doctor is assessing. Overall, our new telehealth platform showed submillimeter accuracy for ptosis and eye motion. In addition, the method showed good results in monitoring muscle weakness, demonstrating that continuous analysis is likely superior to pre-exercise and post-exercise subjective assessment. Conclusions: We demonstrated the ability to objectively quantitate the MG-CE. Our results indicate that the MG-CE should be revisited to consider some of the new metrics that our algorithm identified. We provide a proof of concept involving the MG-CE, but the method and tools developed can be applied to many neurological disorders and have great potential to improve clinical care.