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Step time biofeedback (StepTB) #113

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7 changes: 4 additions & 3 deletions docs/portfolio.md
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Expand Up @@ -45,11 +45,12 @@ We are especially interested in projects supporting researchers, focused on rese
**[Shelter Volunteers](project_shelter_volunteers/about.md)** - Simplify the process of scheduling work shifts for volunteers, and to give homeless shelters visibility into their upcoming staffing.

**[Speech Tagging](project_saltify/about)** - This software transcribes an audio sample into a written format that is accepted by SALT software.


**[Step Time Biofeedback](project_step_time_biofeedback/about)** - This project is focused on developing a tool that leverages force signal data from a Bertec split-belt treadmill to calculate step time and project target zones into a biofeedback system.

**[Where's Religion Desktop](project_wheres_religion_desktop/about.md)** - Where's Religion Desktop is an enhancement on the mobile version which will have extended features.

**[Where's Religion Mobile](project_wheres_religion_mobile/about.md)** - This Project is to create an application for ethnographers to capture the events happening around them along with some audio/visual representation of the event.

**[Where's Religion Mobile](project_wheres_religion_mobile/about.md)** - This Project is to create an application for ethnographers to capture the events happening around them along with some audio/visual representation of the event.

## Current Internal Service Projects

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49 changes: 49 additions & 0 deletions docs/project_step_time_biofeedback/about.md
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---
id: about
title: Step Time Biofeedback
---

<!-- ![Step Time Biofeedback Logo](100x100.jpg) -->

## Overview

The StepTB is a project focused on developing a tool that leverages force signal data from a Bertec split-belt treadmill to calculate step time and project target zones into a biofeedback system. This system is intended to replicate a specific walking perturbation paradigm used in motor and gait learning protocols. The primary aim is to facilitate research comparing explicit (attentional) and implicit (procedural) methods of motor learning, which is crucial for developing optimal interventions for individuals with movement deficits and enhancing human performance.

### Information

- **Source Code:** [https://github.com/oss-slu/Step_Time_Biofeedback](https://github.com/oss-slu/Step_Time_Biofeedback) [<img src="/img/git-alt.svg" alt="git" width="25" height="25" />](https://github.com/oss-slu/Step_Time_Biofeedback)
- **Client:**
- [Dr. Jason Longhurst, Ph.D., PT, DPT, NCS](https://www.slu.edu/doisy/faculty/longhurst-jason.php)
- **Current Tech Lead:** Victor Ojogbane Onoja [<img src="/img/github.svg" alt="github" width="25" height="25" />](https://github.com/jsvoo)
- **Developers:**

- TBD

- **Start Date:** August 2024
- **Adoption Date:** August 2024
- **Technologies Used:**
- TBD
- **Type:** TBD
- **License:** [GNU General Public License v3.0](https://opensource.org/license/gpl-3-0/)

<!-- ### User Guide

Add guide when Type is determined. options include Desktop app, module, package, library

## Technical Information

### Technical Overview

![Software Architecture](architecture.png)

### Development Priorities

- Latest versions of npm, node, and react are essential
- Create a modern-looking user interface
- Incorporate automated testing
- Prioritize version control and collaboration
- Optimize performance -->

## Get Involved

If you would like to contribute to this project, please visit our [GitHub page](https://github.com/oss-slu/Step_Time_Biofeedback) to create your own issues or pull requests.
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