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: Computer Vision Based Fall Detection Methods Using the Kinect Camera : A Survey 
Chapter Title:  - 
1. Abstract of Cited Paper (BIB001):  Three terms are commonly used interchangeably to identify vulnerable older adults: comorbidity, or multiple chronicconditions,frailty, anddisability. However, in geriatricmedicine,there isagrowingconsensusthatthese are distinct clinical entities that are causally related. Each, individually, occurs frequently and has high import clinically. This article provides a narrative review of current understanding of the definitions and distinguishing characteristics of each of these conditions,including theirclinical relevance and distinct prevention and therapeutic issues, and how they are related. Review of the current state of published knowledge is supplemented by targeted analysesin selectedareas where no current publisheddataexists. Overall,the goalof this articleis to providea basis fordistinguishingbetweenthesethreeimportantclinicalconditionsinolderadultsandshowinghowuseofseparate, distinct definitions of each can improve our understanding of the problems affecting older patients and lead to development of improved strategies for diagnosis, care, research, and medical education in this area. 
2. Abstract of Cited Paper (BIB002):  In recent years, we have witnessed a rapid surge in assisted living technologies due to a rapidly aging society. The aging population, the increasing cost of formal health care, the caregiver burden, and the importance that the individuals place on living independently, all motivate development of innovative-assisted living technologies for safe and independent aging. In this survey, we will summarize the emergence of `ambient-assisted living” (AAL) tools for older adults based on ambient intelligence paradigm. We will summarize the state-of-the-art AAL technologies, tools, and techniques, and we will look at current and future challenges. 
3. Abstract of Cited Paper (BIB003):  Fall detection is a major challenge in the public health care domain, especially for the elderly, and reliable surveillance is a necessity to mitigate the effects of falls. The technology and products related to fall detection have always been in high demand within the security and the health-care industries. An effective fall detection system is required to provide urgent support and to significantly reduce the medical care costs associated with falls. In this paper, we give a comprehensive survey of different systems for fall detection and their underlying algorithms. Fall detection approaches are divided into three main categories: wearable device based, ambience device based and vision based. These approaches are summarised and compared with each other and a conclusion is derived with some discussions on possible future work. 
4. Abstract of Cited Paper (BIB004):  The last 20 years have seen ever-increasing research activity in the field of human activity recognition. With activity recognition having considerably matured, so has the number of challenges in designing, implementing, and evaluating activity recognition systems. This tutorial aims to provide a comprehensive hands-on introduction for newcomers to the field of human activity recognition. It specifically focuses on activity recognition using on-body inertial sensors. We first discuss the key research challenges that human activity recognition shares with general pattern recognition and identify those challenges that are specific to human activity recognition. We then describe the concept of an Activity Recognition Chain (ARC) as a general-purpose framework for designing and evaluating activity recognition systems. We detail each component of the framework, provide references to related research, and introduce the best practice methods developed by the activity recognition research community. We conclude with the educational example problem of recognizing different hand gestures from inertial sensors attached to the upper and lower arm. We illustrate how each component of this framework can be implemented for this specific activity recognition problem and demonstrate how different implementations compare and how they impact overall recognition performance.

Literature Review:
The most people with disabilities experience some form of limitation or restriction due to their disability. Those people frequently report that they experience difficulty being independently mobile. And even if they can, they are likely to have some serious accidents such as falls. So, by the appropriate fall detection approach, the fear from fall can be prevented and gives the physical disable person the independent to mobile in his/her room, office or apartment without the help of another person to stay and maintain him\his. Furthermore, in this paper, to be more specific, the target is physically disabled users who use a cane as a mobility aid, also for two reasons: (i) Canes are the most commonly used mobility aids BIB001 . (ii) Physical disability occurs frequently in older adults BIB002 who use the cane regularly, and have the highest risk of death or serious injury arising from a fall; and that risk increases with age BIB001 . Disabled people, in fact, can overcome their disabilities in carrying out daily tasks in many facilities BIB003 . However, for some emergencies like fall which is one of the most frequent emergency, a disabled person requires urgent assistance without an explicitly ask for help. Indeed, according to 2017 statistics from the World Health Organization (WHO) 4 , one out of three 65-year-old people falls each year and, as age increases to 80, the fall occurs each year. And with increases of age, the frequency of falls increases. Furthermore, falls constitute the second leading cause of accidental or injury deaths after injuries of road traffic. These statistics call for efficient and practical\comfortable means to monitor physically disabled people in order to detect falls and react urgently. The most popular Fall Detection (FD) approaches are classified based on the sensor used, and they organize in three categories: wearable device based approaches, ambient sensor-based approaches, and camera (vision) based approaches BIB004 . And because the highly obtrusive of the wearable sensors BIB005 and the uncomfortable during normal daily life activities; and the highly sensing of the ambient sensors which sense the pressure of everything in and around the person and generating too much false alarms BIB004 , this paper considers only camera sensor approaches and more specifically the Kinect camera for its advantages which will discussed later. This survey may help researchers to answer to the following research questions: