Human-Computer Interaction Center, Chair of Communication Science, RWTH Aachen University, 52074 Aachen, Germany.
Sensors (Basel). 2023 Jan 19;23(3):1143. doi: 10.3390/s23031143.
An aged population, increasing care needs, and a lack of (in)formal caregivers represent major challenges for our society today. Addressing these challenges fuels efforts and developments in innovative technologies leading to various existing AAL applications aiming at improving autonomy, independence, and security in older age. Here, the usage of video-based AAL technologies is promising as detailed information can be obtained and analyzed. Simultaneously, this type of technology is strongly connected with privacy concerns due to fears of unauthorized data access or inappropriate use of recorded data potentially resulting in rejection and non-use of the applications. As privacy-preserving visualizations of video data can diminish those concerns, this empirical study examines the acceptance and privacy perceptions of video-based AAL technology applying different visualization modes for privacy preservation (n = 161). These visualization modes differed in their degrees of visibility and identifiability, covering different levels of privacy preservation (low level: "Blurred" mode; medium level: "Pixel" and "Grey" modes; high level: "Avatar" mode) and are specifically evaluated based on realistic video sequences. The results of our study indicate a rather low acceptance of video-based AAL technology in general. From the diverse visualization modes, the "Avatar" mode is most preferred as it is perceived as best suitable to protect and preserve the users' privacy. Beyond that, distinct clusters of future users were identified differing in their technology evaluation as well as in individual characteristics (i.e., privacy perception, technology commitment). The findings support the understanding of potential users' needs for a successful future design, development, and implementation of video-based, but still privacy-preserving AAL technology.
人口老龄化、不断增长的护理需求以及缺乏（正式或非正式）护理人员，这些都是当今社会面临的主要挑战。为了应对这些挑战，人们投入了大量精力并开发了创新技术，从而产生了各种现有的 AAL 应用，旨在提高老年人的自主性、独立性和安全性。在这些应用中，基于视频的 AAL 技术的使用前景广阔，因为可以获取和分析详细信息。与此同时，由于担心未经授权的数据访问或不当使用记录的数据，这种类型的技术与隐私问题密切相关，这可能导致应用被拒绝和不被使用。由于视频数据的隐私保护可视化可以减少这些担忧，因此本实证研究通过应用不同的隐私保护可视化模式（n=161），调查了基于视频的 AAL 技术的接受度和隐私感知。这些可视化模式在可见度和可识别性方面存在差异，涵盖了不同程度的隐私保护（低水平：“模糊”模式；中水平：“像素”和“灰度”模式；高水平：“化身”模式），并根据真实的视频序列进行了具体评估。我们的研究结果表明，人们普遍对基于视频的 AAL 技术的接受度较低。在各种可视化模式中，“化身”模式最受欢迎，因为它被认为是保护和保护用户隐私的最佳模式。除此之外，还确定了不同的未来用户群体，他们在技术评估以及个人特征（即隐私感知、技术承诺）方面存在差异。这些发现支持了对潜在用户需求的理解，这对于成功设计、开发和实施基于视频但仍能保护隐私的 AAL 技术至关重要。
