Contents
Special Issue Topic

Digital Biomarkers: The New Frontier for Medicine and Research

Guest Editor

Dr. Rhoda Au E-Mail

Professor, Anatomy & Neurobiology, Boston University School of Medicine, Boston, USA; Professor, Epidemiology, Boston University School of Public Health, Boston, USA

Research Keywords: Cognition, neuropsychological testing, dementia, Alzheimer’s disease, brain aging, brain health, digital phenotyping, digital biomarkers

About the Special lssue

Precision medicine brings the promise of individualized treatments but doesn’t go far enough. In the U.S., 86% of healthcare related concerns are centered on chronic diseases, the majority of which take years, if not decades, to progress to diagnosis. If we refocus healthcare objectives from detecting and treating disease to optimizing health and identifying indices of change within the realm of normal, available interventions may alter the trajectory of symptoms so dramatically that the diseases never emerge. In this special issue, we seek to highlight how internet connected devices, smartphone applications and advanced analytic methods allow tracking and analyzing health-related behaviors in ways that have not been possible before. These emergent technologies will challenge current gold standards and fuel innovations that will enable solutions that move the primary focus of healthcare from precision medicine to a broader emphasis on precision health.

Keywords: Alzheimer’s disease, brain health, early detection, algorithms, smartphone applications, interconnected devices, advanced computational analytics, disease stratification, precision, digital biomarkers, digital health technologies

Published Articles

Open Access Original Article
Objective measurement of sleep by smartphone application: comparison with actigraphy and relation to self-reported sleep
Aim: Smartphone technology is increasingly used by the public to assess sleep. Specific features of some sleep-tracking applications are comparable to actigraphy in objectively monitoring sleep. The clinical utility of smartphone apps should be investigated further to increase access to convenient means of monitoring sleep.
Published: October 31, 2021 Explor Med. 2021;2:382–391
3571 56 2
Open Access Original Article
Neuropsychological test validation of speech markers of cognitive impairment in the Framingham Cognitive Aging Cohort
Aim: Although clinicians primarily diagnose dementia based on a combination of metrics such as medical history and formal neuropsychological tests, recent work using linguistic analysis of narrative speech to identify dementia has shown promising results. We aim to build upon research by Thomas JA & Burkardt HA et al. (J Alzheimers Dis. 2020;76:905–2) and Alhanai et al. (arXiv:1710.07551v1. 2020) on the Framingham Heart Study (FHS) Cognitive Aging Cohort by 1) demonstrating the predictive capability of linguistic analysis in differentiating cognitively normal from cognitively impaired participants and 2) comparing the performance of the original linguistic features with the performance of expanded features.
Published: June 30, 2021 Explor Med. 2021;2:232–252
3864 70 3
Open Access Original Article
Digital sleep measures and white matter health in the Framingham Heart Study
Aim: Impaired sleep quality and sleep oxygenation are common sleep pathologies. This study assessed the impact of these abnormalities on white matter (WM) integrity in an epidemiological cohort. Methods: The target population was the Framingham Heart Study Generation-2/Omni-1 Cohorts. Magnetic resonance imaging (diffusion tensor imaging) was used to assess WM integrity. Wearable digital devices were used to assess sleep quality: the (M1-SleepImageTM system) and the Nonin WristOx for nocturnal oxygenation. The M1 device collects trunk actigraphy and the electrocardiogram (ECG); sleep stability indices were computed using cardiopulmonary coupling using the ECG. Two nights of recording were averaged.
Published: June 30, 2021 Explor Med. 2021;2:253–267
3765 55 10
Open Access Original Article
Proof of concept: digital clock drawing behaviors prior to transcatheter aortic valve replacement may predict length of hospital stay and cost of care
Aims: Reduced pre-operative cognitive functioning in older adults is a risk factor for postoperative complications, but it is unknown if preoperative digitally-acquired clock drawing test (CDT) cognitive screening variables, which allow for more nuanced examination of patient performance, may predict lengthier hospital stay and greater cost of hospital care.
Published: March 05, 2021 Explor Med. 2021;2:110–121
4585 42 3
Open Access Original Article
Assessing the capacity for mental manipulation in patients with statically-determined mild cognitive impairment using digital technology
Aims: Prior research employing a standard backward digit span test has been successful in operationally defining neurocognitive constructs associated with the Fuster’s model of executive attention. The current research sought to test if similar behavior could be obtained using a cross-modal mental manipulation test.
Published: February 28, 2021 Explor Med. 2021;2:86–97
4068 29 2
Open Access Original Article
Detection of mild traumatic brain injury in pediatric populations using BrainCheck, a tablet-based cognitive testing software: a preliminary study
Aim: Despite its high frequency of occurrence, mild traumatic brain injury (mTBI), or concussion, is difficult to recognize and diagnose, particularly in pediatric populations. Conventional methods to diagnose mTBI primarily rely on clinical questionnaires and sometimes include neuroimaging or pencil and paper neuropsychological testing. However, these methods are time consuming, require administration/interpretation from health professionals, and lack adequate test sensitivity and specificity.
Published: December 31, 2020 Explor Med. 2020;1:396–405
3693 85 1
Open Access Original Article
Identification of digital voice biomarkers for cognitive health
Aim: Human voice contains rich information. Few longitudinal studies have been conducted to investigate the potential of voice to monitor cognitive health. The objective of this study is to identify voice biomarkers that are predictive of future dementia. Methods: Participants were recruited from the Framingham Heart Study. The vocal responses to neuropsychological tests were recorded,
Published: December 31, 2020 Explor Med. 2020;1:406–417
4849 103 27
Open Access Original Article
Using machine intelligence to uncover Alzheimer’s disease progression heterogeneity
Aim: Research suggests that Alzheimer’s disease (AD) is heterogeneous with numerous subtypes. Through a proprietary interactive ML system, several underlying biological mechanisms associated with AD pathology were uncovered. This paper is an introduction to emerging analytic efforts that can more precisely elucidate the heterogeneity of AD. Methods: A public AD data set (GSE84422) consisting of transcriptomic data of postmortem brain samples from healthy controls (n = 121) and AD (n = 380) subjects was analyzed.
Published: December 31, 2020 Explor Med. 2020;1:377–395
5188 91 7
Open Access Commentary
The need for a harmonized speech dataset for Alzheimer’s disease biomarker development
This commentary is the product of a concerted effort to understand the needs, barriers, and gaps in the field of speech and language biomarkers for Alzheimer’s disease (AD). It distills interviews, surveys, and extensive correspondence with global leaders in the areas of dementia research, clinical trials, linguistics, and data analytics into an idealized clinical-study design for the harmonized collection of voice recordings.
Published: December 31, 2020 Explor Med. 2020;1:359–363
4656 116 1
Open Access Original Article
Going against the norm: validation of a novel alternative to brain SPECT normative datasets
Aim: Quantitative analysis of brain single photon emission computed tomography (SPECT) perfusion imaging is dependent on normative datasets that are challenging to produce. This study investigated the combination of SPECT neuroimaging from a large clinical population rather than small numbers of controls. The authors hypothesized this “population template” would demonstrate noninferiority to a control dataset, providing a viable alternative for quantifying perfusion abnormalities in SPECT neuroimaging. Methods: A total of 2, 068 clinical SPECT scans were averaged to form the “population template”. Validation was three-fold. First, the template was imported into SPECT brain analysis software, MIMneuro®, and compared against its control dataset of 90 individuals through its region and cluster analysis tools.
Published: October 30, 2020 Explor Med. 2020;1:331–354
4751 51 0