# User Friendly Implementation for Efficiently Conducting Hammersmith Infant Neurological Examination

**Authors:** D. P. Dogra, K. Nandam, A. K. Majumdar, S. Suralt, J. Mukhopadhyay, B. Majumdar, A. Singh, S. Mukherjee  
**arXiv:** [1402.0698](https://arxiv.org/abs/1402.0698)  
**Date:** 2014-02-04  
**Summary page:** https://www.summarizepaper.com/en/paper/1402.0698v1/

## Key points

- A semi-automatic application has been developed to assist doctors in conducting the Hammersmith Infant Neurological Examination (IDNE) more efficiently.
- The IDNE is a neurological assessment used to diagnose infants with neurological disorders.
- The study focuses on designing a simplified version of the examination that provides quantitative results.
- The application includes a methodology for conducting the IDNE exam that is suitable for inexperienced staff and can be applied to both neonatal and post-neonatal infants.
- Doctors can access previous patient records, which can aid in diagnosing patients with a high risk of neurological disorder.
- The proposed approach for skeleton generation is semi-automatic, increasing the efficiency of conducting the IDNE using the application.
- The developed application has been installed in hospitals and is currently operational.
- It is expected to improve the accuracy of diagnosing neurological disorders in infants by providing quantitative results and facilitating access to patient records.

## Summary

This research aims to develop a semi-automatic application that can assist doctors in conducting the Hammersmith Infant Neurological Examination (IDNE) more efficiently. The IDNE is a neurological assessment used to diagnose infants with neurological disorders, and this study focuses on designing a simplified version of the examination that provides quantitative results. The application includes a methodology for conducting the IDNE exam that is suitable for inexperienced staff and can be applied to both neonatal and post-neonatal infants. Additionally, it allows doctors to access previous patient records, which can aid in diagnosing patients with a high risk of neurological disorder. The proposed approach for skeleton generation is semi-automatic, increasing the efficiency of conducting the IDNE using the application. The developed application has been installed in hospitals and is currently operational. It is expected to improve the accuracy of diagnosing neurological disorders in infants by providing quantitative results and facilitating access to patient records.