Falls are a major health problem with one in three people over the age of 65 falling each year, oftentimes causing hip fractures, disability, reduced mobility, hospitalization and death. A major limitation in fall detection algorithm development is an absence of real-world falls data. Fall detection algorithms are typically trained on simulated fall data that contain a well-balanced number of examples of falls and activities of daily living. However, real-world falls occur infrequently, making them difficult to capture and causing severe data imbalance.

This dataset is in support of my Research paper 'Design of 6-DoF Combat Quadcopter'.

Preprint:   

The system is basic, on existing designs.It is very simple for any graduate,degree holder.

Related Claim : Novel ß Non-Linear Theory

This is a two-part open-access page -'Data:B-Bio Models-1 and 'Data:B-Bio Models-2'. This webpage contains datasets and models, with clinical investigation in simulation, proposed by me which are Self-Claimed advancements. All the content can be freely downloaded after sign-up. 

I. Novel B-Bio Models  

To freely download, pls. click on title.  Make sure you have read My ORCid, Disclaimer and Legal Disclosure Statement.

A medium-scale synthetic 4D Light Field video dataset for depth (disparity) estimation. From the open-source movie Sintel. The dataset consists of 24 synthetic 4D LFVs with 1,204x436 pixels, 9x9 views, and 20–50 frames, and has ground-truth disparity values, so that can be used for training deep learning-based methods. Each scene was rendered with a clean pass after modifying the production file of Sintel with reference to the MPI Sintel dataset.