## 2 Background
### Digital Biomarkers  
The term _biomarker_ refers to objective medical signs that can be accurately and reproducibly measured outside the patient. In contrast, medical symptoms are health or disease indications perceived by patients [55]. Biomarkers can be defined as characteristics that are objectively measured and evaluated as indicators of normal biological processes, pathogenic processes, or pharmacological responses to therapeutic interventions [56]. Biomarkers can include any substance, structure, or process that can be measured from the body and can influence or predict the incidence of the outcome or disease. They can be diverse, from gait cadence and pulse measurements to complex laboratory tests of blood and other tissues [57]. However, the main objective of a biomarker remains to establish the connection between measurable parameters and relevant clinical endpoints [55].  
The type of biomarkers studied in this work are known as _digital biomarkers_. According to the U.S. Food and Drug Administration (FDA), a digital biomarker is a feature or group of features obtained from digital health technologies that are measured to indicate normal biological processes, pathogenic processes, or reactions to exposure or intervention, such as therapeutic interventions [58; 59]. Digital biomarkers are rapidly developing frontier enabled by the availability of sensors and personal devices that can assimilate information about an individual's psychological state, exercise level, cognitive abilities, eating patterns, movement, and tremor [60]. These data are largely derived from sources such as smartphones and portable electronic devices [61].  
Although many additional studies are needed to link digital phenotypes and endpoints with traditional measurements, digital biomarkers have the potential to introduce novel measurements for phenomena that are already in use [62]. Depending on the applications of biomarkers, several types can be identified, such as diagnostic biomarkers (to confirm the presence of a certain disease), monitoring biomarkers (to determine the progression of a disease), pharmacodynamic/response biomarkers (to check the response to certain  
Figure 2: Examples of wearable devices for [PERSON]’s disease management: (**a**) IMU, (**b**) smartwatch, (**c**) smartphone.  
therapies), predictive biomarkers (to know the response to certain medical products) and prognostic biomarkers (to identify the possibility of suffering a certain disease) [63].  
Extracting digital biomarkers involves collecting and analyzing data from digital devices or platforms that can provide insights into physiological, behavioral and cognitive states, in a similar process as shown in Figure 1. These biomarkers can be derived from various sources such as smartphones, wearables, social media, and other digital interactions. The information defined in the biomarker must be meticulously processed and extracted, as raw data is influenced by numerous processes that obscure the underlying signals. To achieve this, various techniques in digital signal processing, statistical analysis, and artificial intelligence are employed to extract and refine the data into a coherent biomarker. Ultimately, these biomarkers undergo validation through clinical studies to ensure their accuracy and reliability in reflecting predicted physiological, behavioral, or cognitive states.