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[NEUES PRODUKT] Webcam Eyetracking Event Classification System (WEECS) API

· 54 min read
Taimur Khan

Adsata stellt heute seinen ersten Microservice zur Verwaltung und Analyse von Webcam-Eyetracking-Daten Dritter vor. Die WEECS API ermöglicht es Nutzern, Fixationen und Sakkaden für ihre eigenen Webcam-Eyetracking-Daten zu erkennen. Der WEECS-Algorithmus erstellt Lebels für rohe Eyetracking-Daten (d.h. x-, y-Koordinaten und Zeitstempel) mit einer hohen Genauigkeit von 80+% (getestet). Dies ist derselbe Algorithmus, den wir auf der Plattform von Adsata verwenden.

Alle Microservices von Adsata werden ĂĽber die RapidAPI-Plattform angeboten: https://rapidapi.com/organization/adsata

Hintergrund​

Eye Tracking ist eine Technik, die verwendet wird, um die Augenbewegungen einer Person zu überwachen, während sie eine Aufgabe ausführt oder sich mit Reizen beschäftigt. Eye-Tracking-Daten bestehen in der Regel aus einer Reihe von zeitgestempelten X- und Y-Koordinaten, die die Position der Augen auf einem Bildschirm oder in der Umgebung darstellen.

Eine gängige Methode zur Analyse von Eye-Tracking-Daten ist die Identifizierung und Unterscheidung von Fixationen und Sakkaden, zwei Arten von Augenbewegungen. Fixierungen beziehen sich auf die Zeitspannen, in denen die Augen relativ still stehen und auf eine bestimmte Stelle gerichtet sind, während Sakkaden die schnellen, ruckartigen Bewegungen bezeichnen, die die Augen zwischen den Fixierungen ausführen.

Im Folgenden werden einige Vorteile der Erkennung von Fixationen und Sakkaden in Eyetracking-Daten aufgefĂĽhrt:

  1. Besseres Verständnis der visuellen Aufmerksamkeit: Durch die Identifizierung von Fixationen und Sakkaden können Forscher Einblicke in die Art und Weise gewinnen, wie Personen ihre visuelle Aufmerksamkeit bei der Ausführung einer Aufgabe oder der Beschäftigung mit Reizen aufteilen. Dies kann bei der Gestaltung effektiverer visueller Anzeigen und Schnittstellen helfen.
  2. Quantifizierung der Aufgabenerfüllung: Die Dauer und Häufigkeit von Fixationen und Sakkaden können als Indikatoren für die Schwierigkeit oder Leichtigkeit einer Aufgabe verwendet werden. Eine längere Fixationsdauer kann beispielsweise darauf hinweisen, dass ein Teilnehmer Schwierigkeiten hat, Informationen zu verarbeiten.
  3. Identifizierung von Bereichen von Interesse: Durch die Analyse von Fixationen können Forscher feststellen, welche Bereiche einer visuellen Darstellung für die Teilnehmer am auffälligsten sind und welche Bereiche ignoriert werden. Diese Informationen können bei der Optimierung von visuellen Anzeigen und Werbung helfen.
  4. Vergleich von Gruppen: Der Vergleich von Fixationsmustern zwischen verschiedenen Teilnehmergruppen (z. B. Experten vs. Neulinge) kann Aufschluss über Unterschiede in der kognitiven Verarbeitung oder in den Strategien geben, die zur Bewältigung einer Aufgabe eingesetzt werden.
  5. Diagnose von Augenkrankheiten: Die Analyse von Fixationsmustern kann auch bei der Diagnose von Augenerkrankungen wie Legasthenie, Aufmerksamkeitsdefizit-Hyperaktivitätsstörung (ADHS) und Autismus-Spektrum-Störungen eingesetzt werden.

Anwendungsfälle​

Die Analyse von Fixationen und Sakkaden in Eyetracking-Daten hat viele praktische Anwendungsfälle. Hier sind einige Beispiele:

  1. Marktforschung: Eye Tracking wird häufig in der Marktforschung eingesetzt, um festzustellen, welche Bereiche einer Produktverpackung oder einer Werbung für die Kunden am auffälligsten sind. Die Fixationsanalyse kann Aufschluss über die Wirksamkeit einer Marketingkampagne geben und Unternehmen bei der Optimierung ihrer visuellen Darstellungen und Werbung helfen.
  2. Gestaltung von Benutzeroberflächen: Die Fixationsanalyse kann auch bei der Gestaltung von Benutzeroberflächen für Software oder Websites eingesetzt werden. Indem sie ermitteln, welche Bereiche der Benutzeroberfläche am häufigsten fixiert werden, können Designer das Layout und das Design im Hinblick auf Benutzerfreundlichkeit und maximale Benutzeraktivität optimieren.
  3. Medizinische Diagnose: Eye Tracking wird auch in der medizinischen Diagnose eingesetzt, insbesondere bei Störungen wie Legasthenie, Autismus-Spektrum-Störungen und Aufmerksamkeitsdefizit-/Hyperaktivitätsstörung (ADHS). Durch die Analyse der Fixationsmuster können Ärzte Einblicke in die kognitiven Prozesse der Patienten gewinnen und geeignete Behandlungsstrategien festlegen.
  4. Training und Ausbildung: Die Blickverfolgung kann auch in der Aus- und Weiterbildung eingesetzt werden, um festzustellen, welche Lehrmaterialien und -techniken fĂĽr verschiedene Lernende am effektivsten sind. Die Fixationsanalyse kann Aufschluss darĂĽber geben, welche visuellen Hinweise und Lernressourcen am effektivsten sind, um die Lernenden zu fesseln und das Lernen zu erleichtern.
  5. Human Factors Engineering: Eye Tracking wird häufig in der Human Factors Engineering eingesetzt, um Anzeigen und Schnittstellen für komplexe Systeme wie Luftfahrt- oder Militäranwendungen zu optimieren. Die Fixationsanalyse kann den Ingenieuren helfen, Displays zu entwerfen, die einfach zu bedienen sind und die kognitive Belastung der Bediener reduzieren.
  6. Psychologie und neurowissenschaftliche Forschung: Die Blickverfolgung wird in der psychologischen und neurowissenschaftlichen Forschung häufig zur Untersuchung von Aufmerksamkeit, Wahrnehmung und Kognition eingesetzt. Durch die Analyse von Fixationsmustern können Forscher Einblicke in die kognitiven Prozesse gewinnen, die dem menschlichen Verhalten und der Entscheidungsfindung zugrunde liegen.

Beispiel für eine NodeJS-API-Request​

Request​

const axios = require("axios");

const options = {
method: "POST",
url: "https://weecs.p.rapidapi.com/classify",
headers: {
"content-type": "application/json",
"X-RapidAPI-Key": "SIGN-UP-FOR-KEY",
"X-RapidAPI-Host": "weecs.p.rapidapi.com",
},
data: 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};

axios
.request(options)
.then(function (response) {
console.log(response.data);
})
.catch(function (error) {
console.error(error);
});

Response​

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