← Back to all news
arXiv Machine Learning By Edwin Rios, Antony Garcia, Fengpei Yuan, Xinming Huang

Smart Insole Human Activity Recognition for Continuous Monitoring in Elderly Care

Read the original on arXiv Machine Learning →

The paper introduces a wireless smart insole that uses 16 pressure sensors and a six‑axis IMU to detect sitting, standing, walking, and unstable walking. Data from 15 healthy adults were processed in overlapping windows and evaluated with participant‑independent cross‑validation, achieving macro‑F1 scores of 0.954–0.980 using Histogram‑Based Gradient Boosting. A compact 1D‑CNN performed similarly but did not significantly outperform the gradient‑boosting model.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

Related stories

arXiv AI
Sep 10

RevalExo: A Functional Daily-Activity Benchmark for Inertial and Visual Locomotion Mode Recognition in Older Adults and Clinical Cohorts

RevalExo is a new benchmark for locomotion mode recognition that focuses on functional daily activities performed by older adults and clinical cohorts. It includes 27 participants from three groups—healthy older adults, stroke survivors, and older adults with probable sarcopenia—recorded with lower-body IMUs and, for a subset, synchronized egocentric video. The dataset offers 10.1 hours of frame‑level annotations across 11 locomotion modes, and the authors evaluate unimodal, multimodal, cross‑population, and cross‑modal recognition challenges, finding that sensor fusion improves performance but transitions and generalization remain difficult.

By Diwas Lamsal, Juha Carlon, Reinhard Claeys, Maxim Yudayev, Louis Flynn, Tom Verstraten, David Beckw\'ee, Eva Swinnen, Mihai B\^ace, Bart Vanrumste, Benjamin Filtjens
roboticsmultimodalbenchmarks
More like this →
arXiv Computer Vision
Aug 25

Predicting Multiple Clinical Outcomes Related to Functional Recovery and Social Isolation Among Older Adults After Lower-Limb Fracture or Hip Replacement

arXiv:2608.23531v1 Announce Type: new Abstract: Older adults recovering after lower-limb fracture or hip replacement may experience complex recovery trajectories. Most of the time, these clinical asp...

By Santosh Ray, Pratik K. Mishra, Ali Abedi, Charlene H. Chu, Amir Ahmad, Shehroz S. Khan
multimodal
More like this →
arXiv Machine Learning
Aug 5

Sedentary Behavior Classification for Wearable Sensors with a CNN-BiLSTM Model

arXiv:2608. 02946v1 Announce Type: new Abstract: Accurate detection of sedentary behavior is important for studying health risks related to prolonged sitting, but posture-based classification remains challenging with wearable sensors, especially at the wrist.

By Yuliang Chen, Weiwei Shi, Jingjing Zou, Rong Zablocki, Animesh Kumar, Jordan A. Carlson, Sheri J. Hartman, Mikael Anne Greenwood-Hickman, Paul R. Hibbing, Marta Jankowska, Jay Yang, Arun Kumar, Loki Natarajan
llmsfine-tuning
More like this →