Autism spectrum disorder (ASD) is a developmental disability that can cause significant social, communication, and behavioral challenges. People with ASD often have problems with social, emotional, and communication skills. In addition, various challenging behavior events are a problem at the community and family levels, making life difficult for autistic people and their environment. The causes of these events can be many and depend on the person and their current condition. This includes unexpected changes in the environment of the person or sensory stimuli that are not even noticeable to typical people - but at least they are not disturbing. Monitoring the physiological changes associated with negative emotions in people with ASD can support caregivers by giving them insights into the internal emotional changes in a real-time fashion. It makes it possible to act as early as possible to prevent the formulation of behavioral problems. With the development of modern personal Information and Communication Technology (ICT) devices (e.g., smartphones, smartwatches, smart bands), wearable sensors have become ubiquitous, and their usage has become part of our everyday lives. This paper provides a protocol for a scoping review of the literature, focusing on the performance of wearable physiological sensors and associated algorithms used for detecting or predicting challenging behavior events in persons with ASD.