10 citations · 15 across the 6 of their papers we have counts for
6 papers
Beyond Simulated Benchmarks: Evaluating Motion Representations for Fall Detection Under Real-World Data Scarcity
Timilehin B. Aderinola, Ilaria D'Ascanio, Luca Palmerini +5
Falls are a major health concern for older adults, and wearable sensors have been widely explored for detecting falls and enabling timely intervention. However, real-world falls ar…
Watch Your Step: A Cost-Sensitive Framework for Accelerometer-Based Fall Detection in Real-World Streaming Scenarios
Timilehin B. Aderinola, Luca Palmerini, Ilaria D'Ascanio +5
Real-time fall detection is crucial for enabling timely interventions and mitigating the severe health consequences of falls, particularly in older adults. However, existing method…
Machine Vision-Enabled Sports Performance Analysis
Timilehin B. Aderinola, Hananeh Younesian, Cathy Goulding +3
This study investigates the feasibility of monocular 2D markerless motion capture (MMC) using a single smartphone to measure jump height, velocity, flight time, co…
An Examination of Wearable Sensors and Video Data Capture for Human Exercise Classification
Ashish Singh, Antonio Bevilacqua, Timilehin B. Aderinola +5
Wearable sensors such as Inertial Measurement Units (IMUs) are often used to assess the performance of human exercise. Common approaches use handcrafted features based on domain ex…
Quantifying Jump Height Using Markerless Motion Capture with a Single Smartphone
Timilehin B. Aderinola, Hananeh Younesian, Darragh Whelan +2
Goal: The countermovement jump (CMJ) is commonly used to measure lower-body explosive power. This study evaluates how accurately markerless motion capture (MMC) with a single smart…
Gait-based Age Group Classification with Adaptive Graph Neural Network
Timilehin B. Aderinola, Tee Connie, Thian Song Ong +2
Deep learning techniques have recently been utilized for model-free age-associated gait feature extraction. However, acquiring model-free gait demands accurate pre-processing such…