## 3 Related Work  
### IoMT Authentication  
The authors of [19] proposed a secure Lightweight Authentication Scheme (LAS) for IoMT-based healthcare systems, enhancing security in healthcare systems. The proposed system required device registration and central authority approval but allowed peer-to-peer communication without central intervention during authentication and communication phases while outperforming other lightweight schemes. However, only the technical part of the scheme was evaluated. A graphical-password-based user authentication scheme for the IoMT to improve security and user experience during the COVID-19 pandemic was proposed in [58]. The proposed scheme, implemented via an Android application, was assessed for system, information, and interface quality using the Post-Study System Usability Questionnaire (PSSUQ) tool, demonstrating its potential to enhance user authentication experiences in healthcare. Similarly, some authors [21] proposed an improved lightweight user authentication scheme for the Internet of Medical Things (IoMT) in which the hash function and XOR operation were used for operation in low-spec healthcare IoT sensors. The proposed scheme outperformed other protocols in terms of security and performance but did not deal with smartphone sensors. The protection of patient information's confidentiality in IoT gadgets was proposed in [22], which used decentralized identifiers (DIDs) and verifiable credentials (VCs) together with OAuth-based authorization framework. The proposed framework demonstrated enhanced privacy and security through a smart pill dispenser, thereby streamlining access control administration. The work, however, mainly focused on the technical part of the model rather than the user part. A study [59] proposed a multi-factor authentication system for IoT-based Wireless Medical Sensor Networks, enhancing security, scalability, and effectiveness in patient care. The proposed system, while offering enhanced functionality and resistance to common attacks, did not include smartphones. The use of Artificial Intelligence (AI) to enhance authentication of IoT users through the design of a framework using bioelectrical signals for authentication and AI with contextual data was proposed in [23]. The framework enhanced security in healthcare, maintained user trust and data integrity, balanced usability and security, and was adaptable to various devices. Their work, however, was only restricted to bioelectrical signals. Most works on the IoMT involving the elderly looks at applications that monitor their health and maintain their well-being without looking at authentication. We now look at other works in the realm of the IoMT that do not necessarily look at the elderly's authentication. Authors [20] suggested an assessment framework to offer trustworthy and safe authentication procedures based on authentication features for Internet of Health Things (IoHT) devices. Using a hybrid multi-criteria decision-making methodology, the framework assessed authentication aspects and determined which authentication scheme or method was best. The work, though adaptive, did not consider elderly users. A biometric-based authentication scheme for hospital environments where patients interacted with smart surroundings without explicit gadgets was proposed in [60]. The scheme could resist various well-known attacks showing that biometric keys were crucial for identification and authentication, but the work generalized security and did not focus on the elderly. A novel, low-complexity, and resilient remote user authentication system for Internet of Things-enabled healthcare applications was presented in [61]. A formal verification proved the security of the scheme and its applicability in real-world healthcare applications. On the other hand, the exploration of authentication techniques for IoT-enabled healthcare systems at different network levels and a taxonomy of attacks was conducted in [62]. Their work focused on user and device verification but did not focus on elderly users.