Smart Glasses for Gait Analysis of Parkinson’s Disease Patients

Kiprijanovska, Ivana; Panchevski, Filip; Stankoski, Simon; Gjoreski, Martin; Archer, James; Broulidakis, John; Mavridou, Ifigeneia; Hayes, Bradley; Guerreiro, Tiago; Gjoreski, Hristijan

doi:10.23919/mipro57284.2023.10159926

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…Additionally, the studies highlight the practicality of the glasses in tracking various behaviours associated with daily activities such as social interaction, movement, dining, leisure activities, and personal care within a home setting [8]. The glasses have also been evaluated in clinical studies for estimating gait parameters in people with Parkinson's disease [9].…”

Section: Wearables For Behaviour Monitoring In Real-lifementioning

confidence: 99%

Smartglasses for Behaviour Monitoring: Recognizing Facial Expressions, Daily Activities, and Eating Habits

Gjoreski,

Sazdov,

Stankoski

et al. 2024

Intelligent Environments 2024: Combined Proceedings of Workshops and Demos &Amp; Videos Session

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The paper presents novel smartglasses for behaviour monitoring by recognizing facial expressions, daily activities, and eating habits. This is achieved by using advanced machine learning algorithms, which interpret the data provided by the sensors located in the frame of the glasses. In particular, the system comprises of 6 optical tracking non-contact sensors, 3 optical proximity sensors, an IMU, and a pressure sensor. The multi-sensor data is then analysed and interpreted by advanced data-fusion and machine algorithms, which recognize facial expressions, activities, and eating behaviour in real time. We will demonstrate how the system is used in practice, i.e., a participant will wear the smartglasses and will interact with the laptop or mobile device by doing facial gestures and expressions. Each of the three use cases will be presented: facial expression recognition, activity recognition, eating detection.

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Section: Wearables For Behaviour Monitoring In Real-lifementioning

confidence: 99%

Smartglasses for Behaviour Monitoring: Recognizing Facial Expressions, Daily Activities, and Eating Habits

Gjoreski,

Sazdov,

Stankoski

et al. 2024

Intelligent Environments 2024: Combined Proceedings of Workshops and Demos &Amp; Videos Session

View full text Add to dashboard Cite

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Use of head-mounted inertial sensors for mobility tasks: Protocol for a Scoping Review (Preprint)

Sloan,

Wallace,

Goubran

et al. 2024

Preprint

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BACKGROUND Human activity recognition, or HAR, is a burgeoning field that uses sensor technology to detect and categorize human movement. Detecting when an activity is happening can be used to break down signals into information about a person’s physical health. Used in combination with HAR are mobility tasks like sit-to-stands (STS), timed-up-and-go (TUG), and others. Together HAR and mobility tasks are an effective method to measure health, especially in older adults. Consumer wearables like FitBits and Apple watches are currently being used to measure many of these mobility tasks. The wide adoption of these devices is a result of their ease of use and simplicity. Despite this, most wearables go unused shortly after purchase. A potential solution is the use of consumer devices which are already adopted like headphones or hearing aids. These devices can perform the same measurements as the wearables but have the advantage of being used for other OBJECTIVE This scoping review will be guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. There is no time limit to when the papers must have been published. The databases included in the search are PubMed, Engineering Village, SCOPUS, and Web of Science. Using pre-established inclusion and exclusion criteria, two reviewers will screen each paper. We will follow the three stages of the screening process: abstract and title screening, full text screening, and full text data extraction. METHODS This scoping review will be guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. There is no time limit to when the papers must have been published. The databases included in the search are PubMed, Engineering Village, SCOPUS, and Web of Science. Using preestablished inclusion and exclusion criteria, two reviewers will screen each paper. We will follow the three stages of the screening process: abstract and title screening, full text screening, and full text data extraction. RESULTS Head-mounted devices have become part of everyday life and many already contain accelerometers. This scoping review will examine how accelerometers have already been used in research to measure mobility tasks, and to answer how consumer devices can be adapted to improve the lives of regular people. CONCLUSIONS Head-mounted devices have become items that are used daily, many already containing accelerometers. This scoping review will answer how accelerometers have already been used in research, and how consumer devices can be adapted to improve the lives of regular people.

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Smart Glasses for Gait Analysis of Parkinson’s Disease Patients

Cited by 2 publications

References 22 publications

Smartglasses for Behaviour Monitoring: Recognizing Facial Expressions, Daily Activities, and Eating Habits

Smartglasses for Behaviour Monitoring: Recognizing Facial Expressions, Daily Activities, and Eating Habits

Use of head-mounted inertial sensors for mobility tasks: Protocol for a Scoping Review (Preprint)

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