ArticleIEEE journal of biomedical and health informatics2015
Posture and activity recognition and energy expenditure estimation in a wearable platform.
Article in IEEE journal of biomedical and health informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Human Posture Estimation: A Systematic Review on Force-Based Methods-Analyzing the Differences in Required Expertise and Result Benefits for Their Utilization.Sensors (Basel, Switzerland) · 2023Pooled it
- FPGA-Based Weighted DTW Framework with Hybrid Gait Symmetry Index for Real-Time Wearable Gait Classification.Sensors (Basel, Switzerland) · 2026Article
- Integrating Sensory Perception and Wearable Monitoring to Promote Healthy Aging: A New Frontier in Nutritional Personalization.Nutrients · 2026Review
- Classification of daily activities using a wireless instrumented insole (WalkinSense) in a semi free-living setting.PloS one · 2026Article
- Human-in-the-Loop Optimization of Knee Exoskeleton Assistance for Minimizing User's Metabolic and Muscular Effort.Sensors (Basel, Switzerland) · 2024Article
- A CNN Model for Physical Activity Recognition and Energy Expenditure Estimation from an Eyeglass-Mounted Wearable Sensor.Sensors (Basel, Switzerland) · 2024Article
- Human Activity Recognition in a Free-Living Environment Using an Ear-Worn Motion Sensor.Sensors (Basel, Switzerland) · 2024Article
- HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics.Sensors (Basel, Switzerland) · 2023Article
- Gait analysis using digital biomarkers including smart shoes in lumbar spinal canal stenosis: a scoping review.Frontiers in medicine · 2023Article
- Ambient and Wearable Sensor Technologies for Energy Expenditure Quantification of Ageing Adults.Sensors (Basel, Switzerland) · 2022Article
- Assessing Impact of Sensors and Feature Selection in Smart-Insole-Based Human Activity Recognition.Methods and protocols · 2022Article
- Wearable Sensors and Machine Learning for Hypovolemia Problems in Occupational, Military and Sports Medicine: Physiological Basis, Hardware and Algorithms.Sensors (Basel, Switzerland) · 2022Review
- The potential of artificial intelligence in enhancing adult weight loss: a scoping review.Public health nutrition · 2021Article
- Unsupervised Pre-trained Models from Healthy ADLs Improve Parkinson's Disease Classification of Gait Patterns.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2020Article
- Validity of Instrumented Insoles for Step Counting, Posture and Activity Recognition: A Systematic Review.Sensors (Basel, Switzerland) · 2019Review
- Automatic Recognition of Activities of Daily Living Utilizing Insole-Based and Wrist-Worn Wearable Sensors.IEEE journal of biomedical and health informatics · 2018Article
- An Event-Triggered Machine Learning Approach for Accelerometer-Based Fall Detection.Sensors (Basel, Switzerland) · 2017Article
- Energy Expenditure in People with Diabetes Mellitus: A Review.Frontiers in nutrition · 2016Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The use of wearable sensors coupled with the processing power of mobile phones may be an attractive way to provide real-time feedback about physical activity and energy expenditure (EE). Here, we describe the use of a shoe-based wearable sensor system (SmartShoe) with a mobile phone for real-time recognition of various postures/physical activities and the resulting EE. To deal with processing power and memory limitations of the phone, we compare the use of support vector machines (SVM), multinomial logistic discrimination (MLD), and multilayer perceptrons (MLP) for posture and activity classification followed by activity-branched EE estimation. The algorithms were validated using data from 15 subjects who performed up to 15 different activities of daily living during a 4-h stay in a room calorimeter. MLD and MLP demonstrated activity classification accuracy virtually identical to SVM (∼ 95%) while reducing the running time and the memory requirements by a factor of >10 3. Comparison of per-minute EE estimation using activity-branched models resulted in accurate EE prediction (RMSE = 0.78 kcal/min for SVM and MLD activity classification, 0.77 kcal/min for MLP versus RMSE of 0.75 kcal/min for manual annotation). These results suggest that low-power computational algorithms can be successfully used for real-time physical activity monitoring and EE estimation on a wearable platform.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.