Matches in SemOpenAlex for { <https://semopenalex.org/work/W4285228679> ?p ?o ?g. }
Showing items 1 to 100 of
100
with 100 items per page.
- W4285228679 endingPage "13423" @default.
- W4285228679 startingPage "13407" @default.
- W4285228679 abstract "Advances in embedded systems have given rise to integrating several small-size health monitoring devices within daily human life. This trend led to an ongoing extension of wearable sensors in a broad range of applications. Wearable technologies, which are firmly connected with the human body, utilize sensors and machine learning to describe individuals’ physical or psychological routines through activity recognition and human movement. Since wearables are used all day long, the power consumption of these systems needs to be reasonably low. Current research considers that such machine learning methods are trained with fixed properties, including sensor sampling rate and statistical features computed from the time series data. However, in reality, wearables require continuous reconfiguration of their computational algorithms due to the personalized nature of human gait and movement. Furthermore, computational algorithms must become energy- and memory-efficient due to these embedded sensors’ limited power and memory. In this paper, we propose a resource-efficient framework for real-time, continuous, and on-node human activity recognition. Typically activity recognition problem is a multi-class classification problem. However, we suggest transforming this problem based on MET (Metabolic Equivalent of Task) into a hierarchical classification model, providing personalized structure for each individual. We discuss the design and construction of this new configurable classification paradigm. Our results demonstrate that the proposed probabilistic cascading system accuracy for different personalized scenarios varies between 94.5% and 96.9% in detecting activities using a limited memory, while power usage of the system is reduced by as high as 17.2% compared to the traditional methods." @default.
- W4285228679 created "2022-07-14" @default.
- W4285228679 creator A5001759639 @default.
- W4285228679 creator A5007139473 @default.
- W4285228679 creator A5009041021 @default.
- W4285228679 creator A5060369486 @default.
- W4285228679 creator A5070728848 @default.
- W4285228679 date "2022-07-01" @default.
- W4285228679 modified "2023-10-14" @default.
- W4285228679 title "Probabilistic Cascading Classifier for Energy-Efficient Activity Monitoring in Wearables" @default.
- W4285228679 cites W1976018856 @default.
- W4285228679 cites W1994267825 @default.
- W4285228679 cites W2012384201 @default.
- W4285228679 cites W2018569461 @default.
- W4285228679 cites W2026297770 @default.
- W4285228679 cites W2026895797 @default.
- W4285228679 cites W2031805477 @default.
- W4285228679 cites W2037643601 @default.
- W4285228679 cites W2066239727 @default.
- W4285228679 cites W2084553975 @default.
- W4285228679 cites W2104992654 @default.
- W4285228679 cites W2123504417 @default.
- W4285228679 cites W2131147042 @default.
- W4285228679 cites W2134751203 @default.
- W4285228679 cites W2143426320 @default.
- W4285228679 cites W2143630872 @default.
- W4285228679 cites W2146806511 @default.
- W4285228679 cites W2148857358 @default.
- W4285228679 cites W2162555816 @default.
- W4285228679 cites W2170265372 @default.
- W4285228679 cites W2311668763 @default.
- W4285228679 cites W2338565696 @default.
- W4285228679 cites W2407430331 @default.
- W4285228679 cites W2472086136 @default.
- W4285228679 cites W2568993235 @default.
- W4285228679 cites W2761234876 @default.
- W4285228679 cites W2923336951 @default.
- W4285228679 cites W2963183072 @default.
- W4285228679 cites W2965149315 @default.
- W4285228679 cites W2995392496 @default.
- W4285228679 cites W3009411039 @default.
- W4285228679 cites W3043128363 @default.
- W4285228679 cites W3113296961 @default.
- W4285228679 cites W3119760575 @default.
- W4285228679 cites W3133590696 @default.
- W4285228679 cites W3139366947 @default.
- W4285228679 cites W3143148078 @default.
- W4285228679 cites W3165561310 @default.
- W4285228679 cites W3173506890 @default.
- W4285228679 cites W3193585534 @default.
- W4285228679 cites W4252713891 @default.
- W4285228679 doi "https://doi.org/10.1109/jsen.2022.3175881" @default.
- W4285228679 hasPublicationYear "2022" @default.
- W4285228679 type Work @default.
- W4285228679 citedByCount "0" @default.
- W4285228679 crossrefType "journal-article" @default.
- W4285228679 hasAuthorship W4285228679A5001759639 @default.
- W4285228679 hasAuthorship W4285228679A5007139473 @default.
- W4285228679 hasAuthorship W4285228679A5009041021 @default.
- W4285228679 hasAuthorship W4285228679A5060369486 @default.
- W4285228679 hasAuthorship W4285228679A5070728848 @default.
- W4285228679 hasConcept C119701452 @default.
- W4285228679 hasConcept C119857082 @default.
- W4285228679 hasConcept C121687571 @default.
- W4285228679 hasConcept C149635348 @default.
- W4285228679 hasConcept C150594956 @default.
- W4285228679 hasConcept C154945302 @default.
- W4285228679 hasConcept C41008148 @default.
- W4285228679 hasConcept C49937458 @default.
- W4285228679 hasConcept C54290928 @default.
- W4285228679 hasConceptScore W4285228679C119701452 @default.
- W4285228679 hasConceptScore W4285228679C119857082 @default.
- W4285228679 hasConceptScore W4285228679C121687571 @default.
- W4285228679 hasConceptScore W4285228679C149635348 @default.
- W4285228679 hasConceptScore W4285228679C150594956 @default.
- W4285228679 hasConceptScore W4285228679C154945302 @default.
- W4285228679 hasConceptScore W4285228679C41008148 @default.
- W4285228679 hasConceptScore W4285228679C49937458 @default.
- W4285228679 hasConceptScore W4285228679C54290928 @default.
- W4285228679 hasFunder F4320306076 @default.
- W4285228679 hasIssue "13" @default.
- W4285228679 hasLocation W42852286791 @default.
- W4285228679 hasOpenAccess W4285228679 @default.
- W4285228679 hasPrimaryLocation W42852286791 @default.
- W4285228679 hasRelatedWork W2604177921 @default.
- W4285228679 hasRelatedWork W3011192796 @default.
- W4285228679 hasRelatedWork W3133932517 @default.
- W4285228679 hasRelatedWork W3170211675 @default.
- W4285228679 hasRelatedWork W3178681001 @default.
- W4285228679 hasRelatedWork W3201415729 @default.
- W4285228679 hasRelatedWork W3207890561 @default.
- W4285228679 hasRelatedWork W3209425741 @default.
- W4285228679 hasRelatedWork W4226054578 @default.
- W4285228679 hasRelatedWork W4312121147 @default.
- W4285228679 hasVolume "22" @default.
- W4285228679 isParatext "false" @default.
- W4285228679 isRetracted "false" @default.
- W4285228679 workType "article" @default.