As seniors continue to age and look to age in place by utilizing smart devices with sensors, online platforms are a major resource for them and their care givers to socialize and search or look for information on agetech. This comes with a risk as they can be unfairly targeted or influenced in a certain way. Influence refers to information or action that can cause a change in direction, thought or action either positively or negatively, some sort of coordinated manipulation either positively or negatively. There are many influence campaigns propagated through social media and our focus is on information that targets the elderly particularly on the topic of agetech. This paper presents a review of existing work around influence campaigns in general, the methods used in influence detection and the obtained results. To our knowledge none of the existing work has addressed influence campaigns from agetech perspective. With that in mind, we developed a new approach for detecting influence campaigns aimed at agetech using machine learning and classifier calibration. We used machine learning to highlight influence campaign and misinformation in agetech. To develop and evaluate our approach, we collected an agetech dataset consisting of a set of tweets that contain the hashtag agetech. The evaluation yielded encouraging results.