Repository logo
 
Loading...
Profile Picture

Search Results

Now showing 1 - 2 of 2
  • Nyon-data, a fall detection dataset from a hinged board apparatus
    Publication . Dionísio, Rogério Pais; Rosa, Ana Rafaela; Jesus, Cassandra Sofia dos Santos
    Falls are one of the causes of severe hilliness among elders, and the COVID-19 pandemic increased the number of unattended cases because of the social distancing measures. This study aims to create a dataset that collects the data from a 3-axis acceleration sensor fixed on a hinged board apparatus that mimics a human fall event. The datalogging system uses off-the-shelf devices to measure, collect and store the data. The resulting dataset includes data from different angle positions and heights, corresponding to joints of the lower limbs of the human body (ankle, knee, and hip). We use the dataset with a threshold-based fall detection algorithm. The result from the Receiver Operating Characteristic curve shows a good behavior with a mean Area Under the Curve of 0.77 and allow to compute a best threshold value with False Positive Rate of 14.8% and True Positive rate of 89.1%. The optimal threshold value may vary depending on the specific population, activity patterns, and environmental conditions, which may require further customization and validation in real-world settings.
  • Nyon : a ubiquitous fall detection device for elders
    Publication . Jesus, Cassandra Sofia dos Santos; Rosa, Ana Rafaela; Dionísio, Rogério Pais
    Falls are one of the main causes of mortality and morbidity in the elderly worldwide. This had let to the research and development of electronic fall-detection systems. We propose a complete fall-detection system, that combines a wearable device (called Nyon) and a message microservice (for email and SMS) to alert caregiver every time a fall occurs. The wearable uses a simple threshold method and has the capability of search and switch between Wi-Fi and Bluetooth, using the available communication technology when a fall occurs. The results have shown that the wearable autonomy is adequate for a daily use and the server microservices are reliable and deliver a message to the caregiver every time a fall alert occurs. Several improvements are planned to increase the autonomy and range of the wearable device.