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Leslie Cloud

dblp:313/3401 · also Leslie J. Cloud · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Health and well-being technologies · 77% Wearable and physiological sensing · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Health and well-being technologies › health monitoring
parkinson's disease monitoring
0.612022
IMU Sensing Data-Based Kinetic Tremor Detection in Parkinson's Disease Patients · SenSys 2022
Wearable and physiological sensing › motion sensing
IMU sensing
0.212022
IMU Sensing Data-Based Kinetic Tremor Detection in Parkinson's Disease Patients · SenSys 2022

Methods — techniques the papers use, named apart from their topics

data analysis · 0.6
YearPublicationVenuePosition
2022 IMU Sensing Data-Based Kinetic Tremor Detection in Parkinson's Disease Patients
abstract
Tremor is a common symptom among Parkinson's disease (PD) patients at all stages. To measure tremor, we utilized IMU sensing data from the wrists while PD patients were drawing. With 30 patients' IMU sensing data obtained from standard tremor rating scale activities, we conducted data analysis for identifying any tremor episodes and extracting tremor amplitude. In this demo, we demonstrate that our preliminary analysis and results show the potential of measuring kinetic tremors effectively using these methods.
Woosub Jung, Kenneth Koltermann, Noah Helm, Gina Blackwell, Ingrid Pretzer-Aboff, Leslie Cloud, Gang Zhou 0002
SenSys6