Non-Invasive Vital Sign Monitoring
30 works in the bibliography carry this topic. Each used an Axivity accelerometer to collect data, or evaluated one as an instrument.
2026
- Assessment of children’s sleep using thigh-worn Axivity AX3 accelerometers (opens in new tab)
- Feasibility Study of a Novel Method of Contactless Radar Sensing for Sleep Monitoring across Adolescence (8-18yrs): Ambient-Teens (opens in new tab)
- Impact of Helicopter Vibrations on In-Ear PPG Monitoring for Vital Signs—Mountain Rescue Technology Study (MoReTech) (opens in new tab)
2025
- A Methodological Framework for Analyzing and Differentiating Daily Physical Activity Across Groups Using Digital Biomarkers from the Frequency Domain (opens in new tab)
- An Effective Approach for Wearable Sensor-Based Human Activity Recognition in Elderly Monitoring (opens in new tab)
- Estimating the sleep period time window based on a hip-worn accelerometer collected in children and adults (opens in new tab)
- Exploring parameter optimisation in machine learning algorithms for locomotor task discrimination using wearable sensors (opens in new tab)
- Validation and comparative study of the Motus system for accurately identifying movement behaviours using different sampling frequencies (opens in new tab)
- Variability and Reliability of the Axivity AX6 Accelerometer in Technical and Human Motion Conditions (opens in new tab)
2024
- A Machine Learning Model for Predicting Sleep and Wakefulness Based on Accelerometry, Skin Temperature and Contextual Information (opens in new tab)
- Adaptive Hierarchical Classification for Human Activity Recognition Using Inertial Measurement Unit (IMU) Time-Series Data (opens in new tab)
- DeskEmo, A Multi-platform Desktop Software for Remote Control and Monitoring of Hematological Parameters (opens in new tab)
- Facilitating ambulatory heart rate variability analysis using accelerometry-based classifications of body position and self-reported sleep (opens in new tab)
- Nightbeat: Heart Rate Estimation From a Wrist-Worn Accelerometer During Sleep (opens in new tab)
- NiMBaLWear analytics pipeline for wearable sensors: a modular, open-source platform for evaluating multiple domains of health and behaviour (opens in new tab)
- Quantitative Analysis of Mother Wavelet Function Selection for Wearable Sensors-Based Human Activity Recognition (opens in new tab)
- Validation of physical activity levels from shank-placed Axivity AX6 accelerometers in older adults (opens in new tab)
2023
2021
- Efficient embedded sleep wake classification for open-source actigraphy (opens in new tab)
- Manual Annotation of Time in Bed Using Free-Living Recordings of Accelerometry Data (opens in new tab)
- Ultra-Wideband Indoor Positioning and IMU-Based Activity Recognition for Ice Hockey Analytics (opens in new tab)
- Wearable Based Calibration of Contactless In-home Motion Sensors for Physical Activity Monitoring in Community-Dwelling Older Adults (opens in new tab)
2020
2019
2018
2017
Learning deep features for kNN-based human activity recognition.