通过多模态可穿戴传感检测自闭症青少年行为升级前的躁动
Detecting Agitation Before Behavioral Escalation in Autistic Youth Through Multimodal Wearable Sensing
- Vanderbilt University（范德堡大学）
- Vanderbilt University Medical Center（范德堡大学医学中心）
- North Carolina State University（北卡罗来纳州立大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究利用多模态可穿戴传感和基础模型迁移，在自闭症青少年中检测行为升级前的躁动，ROC AUC达0.724，证明个体化躁动可提前检测。
AI中文摘要：
在自闭症青少年中，包括攻击行为、自伤行为和破坏财物在内的挑战性行为发生率高达68%，对青少年及其照护者构成风险。这些行为发作之前通常会出现躁动，这是一种通过动作、发声和自主神经唤醒表现出来的逐渐加剧的痛苦状态。躁动的迹象微妙且因人而异，其自主神经成分在没有仪器的情况下无法察觉。我们在15名自闭症青少年参与的30次临床医生引导的会话中，使用惯性测量单元采集上半身运动数据，通过腕戴设备采集生理数据，并通过领夹式麦克风采集发声数据，同时配以专家行为标注。我们针对每种模态适配了四个预训练基础模型，将每个模型投影到共享的128维空间，并将它们融合成一个统一的群体模型。该模型在临床医生标注的发作起始点检测躁动的ROC曲线下面积为0.724（参与者内置换检验p=0.0005），在发作前30秒时降至0.608。15名参与者中有13名的检测结果优于随机水平。从零开始训练的配置仅达到0.58，而冻结特征和微调特征的表现相当（分别为0.71和0.72）。音频贡献了大部分信号，而仅使用手表的配置接近随机水平。因此，个体化的躁动是可检测的，包括在标注发作之前的未标注时间窗口内，这得益于使用一个共享模型而非每个儿童一个模型的基础模型迁移。
英文摘要：
Challenging behaviors including aggression, self-injury, and property destruction are observed in 68% of autistic youth and pose risks to youth and caregivers. These episodes are preceded by agitation, a rising state of distress expressed through movement, vocalization, and autonomic arousal. Its signs are subtle and individualized, and its autonomic components are invisible without instrumentation. We collected upper-body movement from inertial measurement units, physiology from a wrist-worn device, and vocalizations from lapel microphones across 30 clinician-led sessions with 15 autistic youth, paired with expert behavioral annotations. We adapt four pretrained foundation models, one per modality, project each to a shared 128-dimensional space, and fuse them into a single group model. The model detected agitation with an area under the ROC curve of 0.724 at the clinician-annotated onset (within-participant permutation p=0.0005), declining to 0.608 at 30,s before onset. Thirteen of fifteen participants were above chance. A from-scratch configuration reached only 0.58, while frozen and fine-tuned features performed comparably (0.71 and 0.72). Audio contributed most of the signal, and a watch-only configuration stayed near chance. Individualized agitation is therefore detectable, including in unannotated windows preceding the annotated onset, using foundation-model transfer with one shared model rather than one per child.
