Multimodal sensing and intuitive steering assistance improve navigation and mobility for people with impaired vision

To improve the workout efficiency and to provide the body movement suggestions to users in a “smart gym” environment, we propose to use a depth camera for capturing a user’s body parts and mount multiple inertial sensors on the body parts of a user to generate deadlift behavior models generated by a recurrent neural network structure. The contribution of this paper is trifold: 1) The multimodal sensing signals obtained from multiple devices are fused for generating the deadlift behavior classifiers, 2) the recurrent neural network structure can analyze the information from the synchronized skeletal and inertial sensing data, and 3) a Vaplab dataset is generated for evaluating the deadlift behaviors recognizing capability in the proposed method.

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The effects of impaired vision on simulated driving performance

10.26226/morressier.5785edc8d462b80296c9974a ◽

2016 ◽

Author(s):

Aurora van de Loo

Keyword(s):

Driving Performance ◽

Impaired Vision ◽

Simulated Driving

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SRI's Approach to Multimodal Sensing of Stress for Stress Resiliency Training

10.21236/ada571846 ◽

2012 ◽

Author(s):

Ajay Divakaran ◽

Jeffrey Lubin ◽

Joe Ferraro

Keyword(s):

Multimodal Sensing ◽

Resiliency Training

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A Deep Learning Approach for Human Activities Recognition From Multimodal Sensing Devices

IEEE Access ◽

10.1109/access.2020.3027979 ◽

2020 ◽

Vol 8 ◽

pp. 179028-179038

Author(s):

Isibor Kennedy Ihianle ◽

Augustine O. Nwajana ◽

Solomon Henry Ebenuwa ◽

Richard I. Otuka ◽

Kayode Owa ◽

...

Keyword(s):

Deep Learning ◽

Human Activities ◽

Learning Approach ◽

Multimodal Sensing ◽

Human Activities Recognition

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de Haan, E. (2019). Impaired Vision: How the Visual World May Change After Brain Damage

Perception ◽

10.1177/0301006621991952 ◽

2021 ◽

pp. 030100662199195

Author(s):

Frans Verstraten

Keyword(s):

Brain Damage ◽

Visual World ◽

Impaired Vision

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The effects of seasons and weather on sleep patterns measured through longitudinal multimodal sensing

npj Digital Medicine ◽

10.1038/s41746-021-00435-2 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Stephen M. Mattingly ◽

Ted Grover ◽

Gonzalo J. Martinez ◽

Talayeh Aledavood ◽

Pablo Robles-Granda ◽

...

Keyword(s):

Sleep Duration ◽

Seasonal Effects ◽

Sleep Patterns ◽

Sleep Habits ◽

Sleep Behavior ◽

Weather Effects ◽

Wake Time ◽

Multimodal Sensing ◽

Four Seasons ◽

Local Weather

AbstractPrevious studies of seasonal effects on sleep have yielded unclear results, likely due to methodological differences and limitations in data size and/or quality. We measured the sleep habits of 216 individuals across the U.S. over four seasons for slightly over a year using objective, continuous, and unobtrusive measures of sleep and local weather. In addition, we controlled for demographics and trait-like constructs previously identified to correlate with sleep behavior. We investigated seasonal and weather effects of sleep duration, bedtime, and wake time. We found several small but statistically significant effects of seasonal and weather effects on sleep patterns. We observe the strongest seasonal effects for wake time and sleep duration, especially during the spring season: wake times are earlier, and sleep duration decreases (compared to the reference season winter). Sleep duration also modestly decreases when day lengths get longer (between the winter and summer solstice). Bedtimes and wake times tend to be slightly later as outdoor temperature increases.

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Geriatric Conditions and Functional Disability among a National Community-Dwelling Sample of Older Adults in India in 2017–2018

Geriatrics ◽

10.3390/geriatrics6030071 ◽

2021 ◽

Vol 6 (3) ◽

pp. 71

Author(s):

Supa Pengpid ◽

Karl Peltzer

Keyword(s):

Major Depressive Disorder ◽

Depressive Disorder ◽

Chronic Conditions ◽

Sociodemographic Factors ◽

Community Dwelling ◽

Impaired Hearing ◽

Major Depressive ◽

Impaired Vision ◽

Geriatric Conditions ◽

Impaired Cognition

This study aimed to determine the prevalence of geriatric conditions and their association with disability in older community-dwelling adults in India. The cross-sectional sample consisted of 31,477 individuals (≥60 years) from the Longitudinal Ageing Study in India (LASI) Wave 1 in 2017–2018. Geriatric conditions assessed included injurious falls, impaired cognition, underweight, dizziness, incontinence, impaired vision and impaired hearing. More than two in five participants (44.3%) had no geriatric condition, 32.7% had one, 15.9% two and 7.1% had three or more geriatric conditions; 26.9% were underweight, 14.5% dizziness, 13.7% had impaired vision, 9.6% impaired hearing, 9.3% impaired cognition, 8.2% major depressive disorder, 5.7% injurious falls, 4.0% incontinence, and 7.4% had Activity of Daily Living (ADL) dependencies. In logistic regression analysis, adjusted by sociodemographic factors and the number of chronic conditions, we found a higher number of geriatric conditions, and a higher number of chronic conditions were associated with ADL dependencies. In a model adjusted for sociodemographic factors and the type of chronic conditions, we found that a higher number of geriatric conditions and heart disease, stroke, and bone or joint disorder were positively associated with ADL dependencies. The odds of ADL dependencies increased with impaired cognition, impaired vision, impaired hearing, and major depressive disorder. Impaired cognition, incontinence, impaired vision and major depressive disorder were positively associated with dressing, bathing, eating, transferring, and toileting dependency. In addition, impaired hearing was associated with transferring and toileting dependency. More than half of older adults in India had at least one geriatric condition. The prevalence of geriatric conditions was as high as the prevalence of chronic conditions, which in some cases were associated with disability. Geriatric conditions should be included in health care management.

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