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Found 10 papers, 0 papers with code
Enhancing Food Intake Tracking in Long-Term Care with Automated Food Imaging and Nutrient Intake Tracking (AFINI-T) Technology
Half of long-term care (LTC) residents are malnourished increasing hospitalization, mortality, morbidity, with lower quality of life.
Temporal convolutional networks predict dynamic oxygen uptake response from wearable sensors across exercise intensities
The best performing model encoded 218 s history length (TCN-VO$_2$ A), with 187 s, 97 s, and 76 s yielding less than 3% deviation from the optimal validation loss.
When Segmentation is Not Enough: Rectifying Visual-Volume Discordance Through Multisensor Depth-Refined Semantic Segmentation for Food Intake Tracking in Long-Term Care
We propose a novel deep convolutional encoder-decoder food network with depth-refinement (EDFN-D) using an RGB-D camera for quantifying a plate's remaining food volume relative to reference portions in whole and modified texture foods.
Monocular 3D Sway Tracking for Assessing Postural Instability in Cerebral Hypoperfusion During Quiet Standing
Postural instability is prevalent in aging and neurodegenerative disease, decreasing quality of life and independence.
Towards computer vision powered color-nutrient assessment of pureed food
With one in four individuals afflicted with malnutrition, computer vision may provide a way of introducing a new level of automation in the nutrition field to reliably monitor food and nutrient intake.
A new take on measuring relative nutritional density: The feasibility of using a deep neural network to assess commercially-prepared pureed food concentrations
This DNN imaging system for nutrient density analysis of pureed food shows promise as a novel tool for nutrient quality assurance.
Spatial probabilistic pulsatility model for enhancing photoplethysmographic imaging systems
Here, we developed a continuous probabilistic pulsatility model for importance-weighted blood pulse waveform extraction.
A spectral-spatial fusion model for robust blood pulse waveform extraction in photoplethysmographic imaging
Here, we design and implement a signal fusion framework, FusionPPG, for extracting a blood pulse waveform signal with strong temporal fidelity from a scene without requiring anatomical priors (e. g., facial tracking).
Non-contact hemodynamic imaging reveals the jugular venous pulse waveform
Here, we demonstrate for the first time that the JVP can be consistently observed in a non-contact manner using a novel light-based photoplethysmographic imaging system, coded hemodynamic imaging (CHI).
Non-contact transmittance photoplethysmographic imaging (PPGI) for long-distance cardiovascular monitoring
The results support the hypothesis that long-distance heart rate monitoring is feasible using transmittance PPGI, allowing for new possibilities of monitoring cardiovascular function in a non-contact manner.
