{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T15:51:12Z","timestamp":1782489072295,"version":"3.54.5"},"reference-count":77,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T00:00:00Z","timestamp":1782432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006041","name":"Innovate UK","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006041","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Digit. Health"],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Dementias, including those caused by Alzheimer's Disease (AD), are a leading global cause of death, necessitating improvements in early detection and development of more effective disease-modifying therapies. Well-validated pen-and-paper measures serve as the primary method used for cognitive assessment in research and clinical trials in AD. However, these suffer from rater error, infrequent \u201csnapshot\u201d bias, and have limited sensitivity to early-stage pathology, which presents challenges for measuring efficacy in prevention trials. Recent technological advances offer the potential to measure subtle cognitive changes and account for day-to-day variability through real-world data collection. The Cumulus Neuroscience NeuLogiq\u00ae platform (\u201cthe platform\u201d), is comprised of a wireless electroencephalography (EEG) headset, tablet-based cognitive tasks based on well-established paradigms which were designed to be user-friendly based on patient panel inputs, third party integrations (mood, speech and sleep assessments) and cloud-based analytics. This platform has demonstrated utility in healthy populations and may enable objective, frequent, and patient-centered disease tracking in AD and other CNS disorders.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This paper presents findings from a 52-week study involving individuals with mild AD dementia and healthy controls. Analyses focus on usability (e.g., ease of use ratings and reported technical issues) and feasibility (e.g., adherence; withdrawal rates) of using the platform, unsupervised, in the real-world at home setting and exploring how baseline cognitive status and demographic factors impact platform usability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Longitudinal study data after 12 months offer valuable insights into the feasibility of the platform for patients with mild AD enrolled in long-term studies, such as clinical trials. The participants' high adherence to the protocol underscores the practicality of utilizing the platform in this context. Although participants with dementia reported lower confidence levels (31.6%, N = 18) and encountered some minor technical challenges during the initial home setup (accounting for 16.1% of issues reported in Stage 1), they nonetheless demonstrated strong engagement, achieving an overall adherence rate of 77% across the 52-week study protocol.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>This demonstrates that even participants with dementia remain able and willing to use the EEG headset and complete tablet-based cognitive tasks over a year, from the comfort of their homes.<\/jats:p>\n                  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