PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 13, 2026SHILAP Revista de lepidopterología3 citationsOpen Access

Digital biomarkers for early agitation detection in dementia: a scoping review of emerging wearable and smart technologies for personalized care

AMAlex MalioukisRSR Sterling SneadJMJulia Marczika

Key Points

  • This study aims to evaluate the effectiveness of wearable sensor technologies in detecting agitation in dementia and their impact on personalized care.
  • Conducted a scoping literature review following PRISMA-ScR guidelines.
  • Searched five databases for English-language peer-reviewed studies published from 2016 to 2025.
  • Screened 798 articles down to 13 relevant studies meeting predefined inclusion criteria.
  • Wearable sensors with multimodal data and machine learning effectively detect agitation symptoms.
  • Digital phenotyping captures detailed behavioral patterns associated with agitation.
  • User-centered design is crucial for the adoption of these technologies.

Abstract

Introduction Agitation is a common and burdensome symptom in people with dementia, particularly when compounded by impaired communication, making early detection and effective management difficult. Wearable sensor technologies may offer a promising avenue for supporting real-time behavioral monitoring and personalized care in this context. Objective This study aims to examine the current clinical and technological capabilities of wearable sensor systems for detecting and managing agitation in persons with dementia, to assess whether these technologies can effectively support personalized care. Additionally, it seeks to identify key challenges and opportunities in applying human-centered design principles and tailored interventions to improve outcomes for both patients and caregivers. Methods We conducted a scoping literature review, registered on OSF 1 and guided by PRISMA-ScR guidelines. Five databases—Google Scholar, Scopus, PubMed, PsycINFO, and ACM Digital Library—were searched for English-language peer-reviewed studies published between 2016 and early 2025. From an initial pool of 798 articles, a multi-phase screening process led to a final inclusion of 13 studies that met predefined criteria. Results The reviewed studies demonstrated that wearable sensors, particularly those employing multimodal data and personalized machine learning models, enable reliable detection of agitation symptoms and support timely, tailored interventions. The concept of digital phenotyping emerged as a promising approach for capturing complex behavioral signatures, while user-centered design was identified as essential for adoption and long-term compliance. Discussion The evidence identified in this scoping review indicates that wearable and multimodal sensor technologies may offer promising approaches for monitoring agitation in dementia, while acknowledging that the research remains in early stages. We recommend future research focus on large-scale, longitudinal validation and the expansion of these tools to other populations with communication challenges, such as individuals with autism spectrum disorder or traumatic brain injury. Systematic review registration https://doi.org/10.17605/OSF.IO/DNHYM .

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Malioukis et al. (2026) studied this question.

synapsesocial.com/papers/698ebeb185a1ff6a93016181https://doi.org/10.3389/fneur.2026.1683517
Ask AI
Helpful
Bookmark
Share
View Full Paper