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README.md

Physionet Discovery Spider

Introduction

The Physionet Discovery Spider is a powerful web scraping tool designed to extract biomedical signal data from the PhysioNet database. It enables users to efficiently gather and analyze large volumes of medical research data, facilitating advancements in healthcare analytics and research.

Features

• Comprehensive Data Extraction: Scrape detailed information on biomedical signals.
• Customizable Queries: Tailor searches with specific keywords for targeted results.
• Flexible Item Limits: Control the volume of data extracted per run.
• High-Quality Output: Ensure reliable and accurate data collection.
• User-Friendly Configuration: Simple setup with intuitive input parameters.

Input Parameters

Parameter	Type	Required	Description	Example
Queries	array	No	The queries for the spider. Specify keywords to search within PhysioNet.	["signals"]
item_limit	integer	No	Maximum items to scrape per actor run. Set to 0 for no limit.	10

Example Usage

Input JSON

{
  "Queries": ["signals"],
  "item_limit": 10
}

Output JSON

[
  {
    "keyword": "signals",
    "resource_type": "database",
    "access_type": "lock-open",
    "title": "Surface electromyographic signals collected during long-lasting ground walking of young able-bodied subjects",
    "url": "https://physionet.org/content/semg/1.0.1/",
    "authors": "Francesco Di Nardo, Christian Morbidoni, Sandro Fioretti",
    "description": "The dataset is composed of long-lasting surface electromyographic (sEMG) signals recorded from ten muscles during ground walking of 31 young able-bodied subjects in Movement Analysis Lab, Universit\u00e0 Politecnica delle Marche, Ancona, Italy.",
    "topics": [
      "biomedical signals",
      "muscle recruitment",
      "surface emg signal",
      "walking",
      "gait analysis"
    ],
    "published": "Jan.",
    "version": "1.0.1",
    "visualize_url": null,
    "actor_id": "BG6y3LenBAALUglXc",
    "run_id": "dhOskMnQUGtQa9B67"
  },
  {
    "keyword": "signals",
    "resource_type": "database",
    "access_type": "lock-open",
    "title": "Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB)",
    "url": "https://physionet.org/content/but-pdb/1.0.0/",
    "authors": "Lucie Mar\u0161\u00e1nov\u00e1, Andrea Nemcova, Radovan Smisek, et al.",
    "description": "BUT PDB is an ECG signal database with marked peaks of P waves created for the development, and objective comparison of P wave detection algorithms. The database consists of 50 2-minute 2-lead ECG signal records with various types of pathology.",
    "topics": [
      "p wave",
      "ecg"
    ],
    "published": "Jan.",
    "version": "1.0.1",
    "visualize_url": null,
    "actor_id": "BG6y3LenBAALUglXc",
    "run_id": "dhOskMnQUGtQa9B67"
  },
  {
    "keyword": "signals",
    "resource_type": "code",
    "access_type": "lock-open",
    "title": "Model for Simulating ECG and PPG Signals with Arrhythmia Episodes",
    "url": "https://physionet.org/content/ecg-ppg-simulator-arrhythmia/1.3.1/",
    "authors": "Andrius Solo\u0161enko, Andrius Petr\u0117nas, Birut\u0117 Paliakait\u0117, et al.",
    "description": "A model is capable of simulating sinus rhythm, atrial fibrillation and ectopic beats in ECGs and PPGs as well as extreme bradycardia and ventricular tachycardia in PPGs. Different types of noises and artifacts can also be added to the waveforms.",
    "topics": [
      "arrhythmia",
      "atrial fibrillation",
      "noise",
      "tachycardia",
      "detection",
      "motion artifacts",
      "simulation",
      "bradycardia",
      "ppg",
      "ecg"
    ],
    "published": "Jan.",
    "version": "1.0.1",
    "visualize_url": null,
    "actor_id": "BG6y3LenBAALUglXc",
    "run_id": "dhOskMnQUGtQa9B67"
  }
]

Use Cases

• Market Research and Analysis: Gather data for competitive analysis in the biomedical field.
• Competitive Intelligence: Monitor advancements and publications by competitors.
• Price Monitoring: Track pricing trends of medical devices and services.
• Content Aggregation: Compile comprehensive datasets for research purposes.
• Academic Research: Support studies with extensive biomedical signal data.
• Business Automation: Automate data collection processes for efficiency.

Installation and Usage

1. Search for "Physionet Discovery Spider" in the Apify Store.
2. Click "Try for free" or "Run".
3. Configure input parameters as needed.
4. Click "Start" to begin extraction.
5. Monitor progress in the log.
6. Export results in your preferred format (JSON, CSV, Excel).

Output Format

The output is a JSON array containing objects with the following fields:

• keyword: The search term used.
• resource_type: Type of resource (e.g., database, code).
• access_type: Access level (e.g., lock-open).
• title: Title of the resource.
• url: URL to access the resource.
• authors: List of authors.
• description: Brief description of the resource.
• topics: Relevant topics or tags.
• published: Publication date.
• version: Version number.
• visualize_url: URL for visualization (if available).
• actor_id: Unique identifier for the actor.
• run_id: Unique identifier for the run.

Error Handling

The spider is designed to handle common web scraping errors such as timeouts and missing elements. If an error occurs, it will be logged in the Apify Console for review. Users can adjust settings or contact support for persistent issues.

Rate Limiting and Best Practices

To avoid being blocked by PhysioNet, adhere to rate limiting guidelines:

• Implement delays between requests.
• Respect robots.txt directives.
• Use a reasonable number of concurrent requests.

Limitations and Considerations

• The spider is limited to publicly accessible data on PhysioNet.
• Ensure compliance with PhysioNet's terms of service when using the spider.
• Custom queries may require adjustments for optimal results.

Support

For custom/simplified outputs or bug reports, please contact:

• Email: support@getdataforme.com
• Subject line: "custom support"
• Contact form: Get Data For Me

We're here to help you get the most out of this Actor!