You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Survey on Fall Detection and Fall Prevention Using Wearable and External Sensors 
Chapter Title:  Privacy 
1. Abstract of Cited Paper (BIB001):  We propose an automatic, privacy-preserving, fall detection method for indoor environments, based on the usage of the Microsoft Kinect® depth sensor, in an “on-ceiling” configuration, and on the analysis of depth frames. All the elements captured in the depth scene are recognized by means of an Ad-Hoc segmentation algorithm, which analyzes the raw depth data directly provided by the sensor. The system extracts the elements, and implements a solution to classify all the blobs in the scene. Anthropometric relationships and features are exploited to recognize one or more human subjects among the blobs. Once a person is detected, he is followed by a tracking algorithm between different frames. The use of a reference depth frame, containing the set-up of the scene, allows one to extract a human subject, even when he/she is interacting with other objects, such as chairs or desks. In addition, the problem of blob fusion is taken into account and efficiently solved through an inter-frame processing algorithm. A fall is detected if the depth blob associated to a person is near to the floor. Experimental tests show the effectiveness of the proposed solution, even in complex scenarios.

Literature Review:
One of the main problems of camera-based systems is the fact that people do not like to be watched; they are worried that their intimacy will be violated. Few studies address this issue. The most common way researchers approach this issue is by only sending subjects' images when an alarm is triggered. Ozcan et al. BIB001 developed a fall detection system that utilizes a wearable embedded smart camera that is mounted on the waist of the subject of interest. The camera captures the images of the environment and not the subject's, eliminating the privacy concern. Gasparrini et al. BIB002 developed a fall detection system using a depth camera (Microsoft Kinect). Privacy issues are not a problem due to the fact that this cameras do not recognize the facial characteristics of the subject.