27 citations · 58 across the 9 of their papers we have counts for
11 papers
Enhancing Food Intake Tracking in Long-Term Care with Automated Food Imaging and Nutrient Intake Tracking (AFINI-T) Technology
Kaylen J. Pfisterer, Robert Amelard, Jennifer Boger +3
Half of long-term care (LTC) residents are malnourished increasing hospitalization, mortality, morbidity, with lower quality of life. Current tracking methods are subjective and ti…
Temporal convolutional networks predict dynamic oxygen uptake response from wearable sensors across exercise intensities
Robert Amelard, Eric T Hedge, Richard L Hughson
Oxygen consumption (VO) provides established clinical and physiological indicators of cardiorespiratory function and exercise capacity. However, VO monitoring is largely li…
Optical Hemodynamic Imaging of Jugular Venous Dynamics During Altered Central Venous Pressure
Robert Amelard, Andrew D Robertson, Courtney A Patterson +3
An optical imaging system is proposed for quantitatively assessing jugular venous response to altered central venous pressure. The proposed system assesses sub-surface optical abso…
When Segmentation is Not Enough: Rectifying Visual-Volume Discordance Through Multisensor Depth-Refined Semantic Segmentation for Food Intake Tracking in Long-Term Care
Kaylen J Pfisterer, Robert Amelard, Audrey G Chung +4
Malnutrition is a multidomain problem affecting 54% of older adults in long-term care (LTC). Monitoring nutritional intake in LTC is laborious and subjective, limiting clinical inf…
Monocular 3D Sway Tracking for Assessing Postural Instability in Cerebral Hypoperfusion During Quiet Standing
Robert Amelard, Kevin R Murray, Eric T Hedge +4
Postural instability is prevalent in aging and neurodegenerative disease, decreasing quality of life and independence. Quantitatively monitoring balance control is important for as…
Towards computer vision powered color-nutrient assessment of pureed food
Kaylen J. Pfisterer, Robert Amelard, Braeden Syrnyk +1
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…