Alzheimer’s Disease (AD) represents a major and rapidly growing burden to the healthcare ecosystem. A growing body of evidence indicates that cognitive, behavioral, sensory, and motor changes may precede clinical manifestations of AD by several years. Existing tests designed to diagnose neurodegenerative diseases, while well-validated, are often less effective in detecting deviations from normal cognitive decline trajectory in the earliest stages of the disease. In the quest for gold standards for AD assessment, there is a growing interest in the identification of readily accessible digital biomarkers, which harness advances in consumer grade mobile and wearable technologies. Topics examined include a review of existing early clinical manifestations of AD and a path to the respective sensor and mobile/wearable device usage to acquire domain-centric data towards objective, high frequency and passive digital phenotyping.

Introduction The application of digital monitoring biomarkers in health, wellness and disease management is reviewed. Harnessing the near limitless capacity of these approaches in the managed healthcare continuum will benefit from a systems-based architecture which presents data quality, quantity, and ease of capture within a decision making dashboard. Methods A framework was developed which stratifies key components and advances the concept of contextualized biomarkers. The framework codifies how direct, indirect, composite and contextualized composite data can drive innovation for the application of digital biomarkers in healthcare. Results The de novo framework implies consideration of physiological, behavioral and environmental factors in the context of biomarker capture and analysis. Application in disease and wellness is highlighted, and incorporation in clinical feedback loops and closed loop systems is illustrated. Conclusions The study of contextualized biomarkers has the potential to offer rich and insightful data for clinical decision making. Moreover, advancement of the field will benefit from innovation at the intersection of medicine, engineering and science. Technological developments in this dynamic field will thus fuel its logical evolution guided by inputs from patients, physicians, healthcare providers, end-payors, actuarists, medical device manufacturers, and drug companies.

The pursuit of digital biomarkers wherein signal outputs from biosensors are collated to inform health-care decisions continues to evolve at a rapid pace. In the field of neurodegenerative disorders, a goal is to augment subjective patient-reported inputs with patient-independent verifiable data that can be used to recommend interventive measures. For example, in the case of Alzheimer's disease, such tools might preselect patients in the presymptomatic and prodromal phases for definitive positron emission tomographic analysis, allowing accurate staging of disease and providing a reference point for subsequent therapeutic and other measures. Selection of appropriate and meaningful digital biomarkers to pursue, however, requires deep understanding of the disease state and its ecological relationship to the instrumental activities of daily living scale. Similar opportunities and challenges exist in a number of other chronic disease states including Parkinson's, Huntington's, and Duchenne's disease, multiple sclerosis, and cardiovascular disease. This review will highlight progress in device technology, the need for holistic approaches for data inputs, and regulatory pathways for adoption. The review focuses on published work from the period 2012-2017 derived from online searches of the most widely used abstracting portals.

In the development of sensory prosthetic devices based on intracortical microstimulation (ICMS) an important objective is to optimize the stimulus waveform. However, because of the large design space such optimization is an imposing challenge. This study highlights the ability of individual rats, trained using a conditioned avoidance paradigm and performing an adaptive task, to generate highly consistent and significant data. Three experiments on the effects of phase delay, stimulus pulse rate, and waveform asymmetry were completed and revealed detailed and significant results. These results, consisting of 244 individual thresholds, were generated by one rat in 19 days.

Neuroprosthetics using intracortical microstimulation can potentially alleviate sensory deprivation due to injury or disease. However the information bandwidth of a single microstimulation channel remains largely unanswered. This paper presents three experiments that examine the importance of Peak Power/Charge and RMS Power/Charge for detection of acoustic and electrical Sinusoidal Amplitude Modulated stimuli by the auditory system. While the peripheral auditory system is sensitive to RMS power cues for the detection of acoustic stimuli, here we provide results that suggest that the auditory cortex is sensitive to peak charge cues for electrical stimuli. Varying the modulation frequency and depth do not change this effect for detection of modulated electrical stimuli.