Table 2.
Categories for data extraction.
| Category | Definitions | Reference | |||
| Nature of academic research | |||||
|
|
Verification | Evaluates and demonstrates the performance of a sensor technology within a BioMeTa, and the sample-level data it generates, against a prespecified set of criteria | [16] | ||
|
|
Analytical validation | Evaluates the performance of the algorithm, and the ability of this component of the BioMeT to measure, detect, or predict physiological or behavioral metrics | [16] | ||
|
|
Clinical validation | Evaluates whether a BioMeT acceptably identifies, measures, or predicts a meaningful clinical, biological, physical, functional state, or experience in the stated context of use (which includes a specified population) | [16] | ||
|
|
Measure identification | Research studies to identify key variables from the information extracted from digital sensors, to support decision-making | [20] | ||
|
|
Security | Research studies to assess the risks associated with digital clinical measures and taking necessary measures for information security | [21] | ||
|
|
Data rights and governance | Research studies to assess the data access, privacy, and sharing (following the FAIRb guiding principle) | [22] | ||
|
|
Ethics | Research studies to ensure equity and justice during every step of the development and deployment of digital clinical measures (eg, reduce health disparities or racial injustice) | [23] | ||
|
|
Usability and utility (human factors/behavioral economics) | Research studies to investigate human factors associated with digital clinical measures (eg, how usable, useful, or unobtrusive a digital clinical measure can be for an end user). It involves surveys from the participants on user experience. | [24] | ||
|
|
Standards | Involves standardization of the data extracted from digital clinical measures for interoperability | [25] | ||
|
|
Usability and utility (data visualization) | Involves data visualization/result presentation for all end uses | [24] | ||
|
|
Economic feasibility | Research studies to investigate economic feasibility of a digital clinical measure | [26] | ||
|
|
Operations (care) | Involves clinicians and economists to design clinical workflow and corresponding evaluation that is typically done for a clinical trial | [27] | ||
|
|
Operations (research design) | Involves clinicians and biostatisticians to design a research study and execution plan, which is typically done for a clinical trial via power analysis and statistical analysis plan | [28] | ||
|
|
Operations (research analysis) | Involves analyzing data from digital clinical measures (eg, data analyst or data scientists) | [29] | ||
|
|
Operations (data) | Involves monitoring data and metadata from digital clinical measures (eg, bioinformatics) | [30] | ||
| Digital clinical measures | |||||
|
|
Biochemical | Senses biochemicals (eg, sweat sensor or continuous glucose monitors) | [31] | ||
|
|
Movement and activity | Tracks movement and activity (eg, step count or actigraph) | [31] | ||
|
|
Physiological (electrical) | Senses electrical signals related to physiological phenomena (eg, electrocardiography, electroencephalography, electromyography, bioimpedance, electrodermal activity, or electroooculography) | [32-34] | ||
|
|
Physiological (mechanical) | Senses mechanical signals related to physiological phenomena (eg, phonocardiography, speech, lung sounds, joint acoustic emission, seismocardiography, or ballistocardiography) | [35,36] | ||
|
|
Physiological (optics and imaging) | Senses optical signals related to physiological phenomena (eg, photoplethysmography, camera for blood volume pulse, or bioradar) | [37] | ||
| Funding sources | |||||
|
|
Government | US Government funding agencies | [38] | ||
|
|
Industry | Pharma, tech, and medical device industry | [38] | ||
|
|
Independent foundation | Universities, private nonprofits, societies, and independent associations | [38] | ||
|
|
Unfunded | Investigator initiated with no funding sources explicitly stated |
|
||
aBioMeT: biometric monitoring technology.
bFAIR: Findable, Accessible, Interoperable, and Reusable.