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Hierarchical classification scheme for real-time recognition of physical activities and postural transitions using smartphone inertial sensors.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper introduces a novel approach for real-time classification of human activities using data from inertial sensors embedded in a smartphone. We propose a hierarchical classification scheme to recognize seven classes of activities including post...

Using Elastic Net Penalized Cox Proportional Hazards Regression to Identify Predictors of Imminent Smoking Lapse.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
INTRODUCTION: Machine learning algorithms such as elastic net regression and backward selection provide a unique and powerful approach to model building given a set of psychosocial predictors of smoking lapse measured repeatedly via ecological moment...

Evaluation of Depth Cameras for Use as an Augmented Reality Emergency Ruler.

Studies in health technology and informatics
Children are rarely affected by medical emergencies. The experience of doctors or paramedics with child emergencies is correspondingly poor. The anatomical features and individual calculations make such an emergency much more error-prone than a compa...

SpiroConfidence: Determining the Validity of Smartphone Based Spirometry Using Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Prior work has shown that smartphone spirometry can effectively measure lung function using the phone's built-in microphone and could one day play a critical role in making spirometry more usable, accessible, and cost-effective. Although traditional ...

Determination of Saccade Latency Distributions using Video Recordings from Consumer-grade Devices.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Quantitative and accurate tracking of neurocognitive decline remains an ongoing challenge. We seek to address this need by focusing on robust and unobtrusive measurement of saccade latency - the time between the presentation of a visual stimulus and ...

Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity: The Mobile Parkinson Disease Score.

JAMA neurology
IMPORTANCE: Current Parkinson disease (PD) measures are subjective, rater-dependent, and assessed in clinic. Smartphones can measure PD features, yet no smartphone-derived rating score exists to assess motor symptom severity in real-world settings.

Speech2Health: A Mobile Framework for Monitoring Dietary Composition From Spoken Data.

IEEE journal of biomedical and health informatics
Diet and physical activity are known as important lifestyle factors in self-management and prevention of many chronic diseases. Mobile sensors such as accelerometers have been used to measure physical activity or detect eating time. In many intervent...

The need to approximate the use-case in clinical machine learning.

GigaScience
The availability of smartphone and wearable sensor technology is leading to a rapid accumulation of human subject data, and machine learning is emerging as a technique to map those data into clinical predictions. As machine learning algorithms are in...

IntelliTable: Inclusively-Designed Furniture with Robotic Capabilities.

Studies in health technology and informatics
IntelliTable is a new proof-of-principle assistive technology system with robotic capabilities in the form of an elegant universal cantilever table able to move around by itself, or under user control. We describe the design and current capabilities ...