Detecting self-harming activities with wearable devices
Explore this paper's citation graph
- Type
- article
- Published
- 2015-03-23
- Cited by
- 11
- References
- 20
- OpenAlex
- https://openalex.org/W1553362494
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:17162675
Keywords
Wearable computer, Harm, Schedule, Accelerometer, Computer science
References
- Using Dynamic Time Warping to Find Patterns in Time Series
- Self-harm and attempted suicide within inpatient psychiatric services: a review of the literature.
- Supporting patient monitoring using activity recognition with a smartphone
- Energy-Efficient Continuous Activity Recognition on Mobile Phones: An Activity-Adaptive Approach
- Suicide risk in relation to psychiatric hospitalization: evidence based on longitudinal registers.
- Activity recognition using cell phone accelerometers
- Clinical correlates of inpatient suicide.
- Fast time series classification using numerosity reduction
- Suicide Inside: A Systematic Review of Inpatient Suicides
- An Activity Recognition System For Mobile Phones
- Activity Recognition for the Smart Hospital
- A Survey on Human Activity Recognition using Wearable Sensors
- Human Activity Recognition via an Accelerometer-Enabled-Smartphone Using Kernel Discriminant Analysis
- Searching and Mining Trillions of Time Series Subsequences under Dynamic Time Warping
- The Utility and Effectiveness of 15-minute Checks in Inpatient Settings.
- Lessons from a comprehensive clinical audit of users of psychiatric services who committed suicide.
- Inpatient Suicide: Identifying Vulnerability in the Hospital Setting
- Activity Recognition Using Hierarchical Hidden Markov Models on a Smartphone with 3D Accelerometer
Cited by
- Mobile Health Technologies for Suicide Prevention: Feature Review and Recommendations for Use in Clinical Care
- The role of wrist-mounted inertial sensors in detecting gait freeze episodes in Parkinson's disease
- HealthyOffice: Mood recognition at work using smartphones and wearable sensors
- Watch-Dog: Detecting Self-Harming Activities From Wrist Worn Accelerometers
- Context-based Human Activity Recognition Using Multimodal Wearable Sensors
- #selfharm on Instagram: Quantitative Analysis and Classification of Non-Suicidal Self-Injury
- NLP-UNED at eRisk 2020: Self-harm Early Risk Detection with Sentiment Analysis and Linguistic Features
- A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions
- BeautyNet: A Makeup Activity Recognition Framework using Wrist-worn Sensor
- A Review of Wearables-Based Activities of Daily Living Recognition With LLMs: Overview, Progress, and Trends
- NLP-UNED at eRisk 2021: self-harm early risk detection with TF-IDF and linguistic features
Related papers
- A Survey of the Development of Wearable Devices
- Trust matters: Adoption of wearable technology
- The Wearable Level for Wearable Devices
- Significance of Nanomaterials in Wearables: A Review on Wearable Actuators and Sensors
- Empirical Study on Initial Trust of Wearable Devices Based on Product Characteristics
- Research and Application Progress of Intelligent Wearable Devices
- Flexible and Wearable Power Sources for Next‐Generation Wearable Electronics
- The Internet of Things for Applications in Wearable Technology