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All Journal TEKNIK INFORMATIKA JOIV : International Journal on Informatics Visualization Journal of Applied Data Sciences IJCOSIN : Indonesian Journal of Community Service and Innovation Prosiding Seminar Nasional Universitas Ma Chung Jurnal INFOTEL
Andi Prademon Yunus
Telkom University
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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TelUP Human Fall Dataset: A Motion Forecasting Study of Human Falls Agung Widiyanto; Raphon Galuh Candraningtyas; Andi Hisyam Helmi F.F; Mayesq Prameswari; Himam Bashiran; Geugeut Nyarikawanti Surahmat; Balqis Awaluna Rahmah; Anak Agung Istri Candra Manika Dewi; Andi Prademon Yunus
JURNAL INFOTEL Vol 17 No 3 (2025): August
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i3.1420

Abstract

This study investigates multitask learning approaches for human motion forecasting and fall classification using pose data extracted from video sequences. A custom dataset, the TelUP HumanFall Forecasting Dataset, was developed, containing annotated video frames representing fall and non-fall scenarios captured from six participants. Pose information was extracted using YOLOv11, producing 17 keypoints per frame, which were normalized and segmented into temporal sequences for training. Three deep learning architectures, Multilayer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM), were implemented and evaluated. The models were assessed in a subject-independent test set consisting of two participants to ensure generalization. Quantitative evaluation measured the forecast error using the mean per joint position error (MPJPE) and classification accuracy. The MLP achieved the lowest MPJPE of 0.2630 (131.5 pixels), while the LSTM obtained the highest classification accuracy of 92.89%. Qualitative analysis revealed limitations in the capture of complex joint dynamics. Despite fast training convergence, the results emphasize a trade-off between forecast precision and classification accuracy. Future work will explore more expressive architectures and improved pose extraction methods to enhance forecast realism.
Recurrent Neural Network for Human Fall Motion Prediction Andi Prademon Yunus; Bintang Rizqi Pasha; Yesy Diah Rosita
Prosiding Seminar Nasional Universitas Ma Chung (Informatika & Sistem Informasi Bahasa dan Seni
Publisher : Ma Chung Press

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Falls pose a significant health risk, especially for older adults, where one in three people over 65 experiences a fall each year. For those over 85, the consequences of falls can be severe, leading to life-threatening injuries and a marked decline in quality of life. To address the critical need for fall prevention, this study proposes a prediction approach using Recurrent Neural Networks (RNNs) to recognize patterns in human motion that may indicate an impending fall. By utilizing the CAUCA fall dataset—carefully designed to detect abnormal fall movements—we implemented and assessed different RNN architectures, including Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU). Our findings show that the GRU model performed best, achieving an accuracy of 0.716, MPJPAE of 32.921 pixels, MPJVE of 22.457 pixels per frame, and Euclidean distance metric outperforming the other models, with RNN closely following at an accuracy of 0.716, MPJPAE of 41.872 pixels, MPJVE of 21.44 pixels per frame. These promising results suggest that RNN models, particularly GRU, can serve as valuable tools in predicting falls, offering a foundation for future technology that can help prevent falls before they happen.
Co-Authors Agung Widiyanto Amalia Beladinna Arifa Amalia Suciati Amaliah, Nuuraan Rizqy Anak Agung Istri Candra Manika Dewi Andi Hisyam Helmi F.F Ariq Cahya Wardhana Aulia Desy Nur Utomo Balqis Awaluna Rahmah Bintang Rizqi Pasha Choo, Yit Hong Dany Candra Febrianto Dian Kartika Sari, Dian Kartika Geugeut Nyarikawanti Surahmat Gustalika, Muhammad Azrino Himam Bashiran Kartika Dian Kurniasari Latief, Muhammad Abdul Lim, Chee Peng Low, Alex Mayesq Prameswari Muhamad Azrino Gustalika Muhammad Zuhdi Hanif Nicolaus Euclides Wahyu Nugroho Nuuraan Rizqy Amaliah Raphon Galuh Candraningtyas Rifki Adhitama, Rifki Sim, Kok Swee Sofia, Martryatus Suciati, Amalia Wahyu Andi Saputra wong, Shun Wei Yesy Diah Rosita Yesy Diah Rosita Yit Hong Choo Yit Hong Choo Yit Hong Choo