PRE2023 3 Group5

Medical Robot

Group Members

Name	Student ID	Department
Yuting Dong	1546104	Computer Science
Jie Liu	1799525	Computer Science
Zhiyang Zhang	1841734	Mechanical Engineering
Samir Saidi	1548735	Computer Science
Feiyang Yan	1812076	Computer Science
Nikola Mitsev	1679759	Computer Science

Introduction

Problem Statement

Nowadays, there is an increasing amount of elderly or impaired people whose health conditions or disabilities prevent them from taking care of themselves. Meanwhile, a large number of them have no choice but to live alone entirely or for most of the time. For some people, especially those with limited mobility, even walking in their own home is a struggle. They can easily get hurt if they are not taken care of properly, and there's a likelihood that their family may remain unaware of potential harm. There have been occasions where individuals fall over at home without anyone noticing which might lead to severe consequences. The caretaker is thus a necessary role that must be present in our society to ensure the well-being and quality of life for individuals facing these challenges. However, contemporary families often face the dual dilemma of struggling to allocate time for caregiving responsibilities and encountering financial barriers that hinder their ability to engage professional caregivers. Consequently, a significant portion of the population in need is left without the essential care they require.

Objectives

Considering the current situations that the individuals with limited mobility are facing, we've decided to design a home robot with a primary focus on safety monitoring that is easily accessible to individuals. The robot should be able to have an eye on the individuals while they are walking and take actions when they fall over but couldn't manage to get up on their own. The main goal of the robot is to ensure the safety of the user and reach out for help whenever needed. On one hand, the robot closely monitors the individual's mobility at home and swiftly responding to instances of falls. On the other hand, it enhances the overall safety of individuals living at home and provide peace of mind for both users and their caregivers or family. Moreover, the robot can also easily be applied in public areas such as hospitals or nursing homes for the same purpose. However, it may raise privacy concerns if the data recorded by the robot is not kept secure.

As an initial idea, the design of the robot should cover these features:

1. Built-in program: The robot should be designed as a digital program that can be easily installed on household cameras.

2. Fall Detection and Response System: The robot is implemented with high-accuracy human detection and fall detection artificial intelligence algorithms to detect instances of falls and decision-making abilities to react to the instances accordingly.

3. Emergency Communication: The robot incorporates a communication system that allows itself to alert family members, caregivers, or emergency services in case of a fall that cannot be managed by the users themselves.

4. User-Friendly Interface: A user-friendly interface should be designed for the caregivers or family members, which is preferably an application or a portal that can be installed in smartphones. Alerts and updates can be sent to the smartphones remotely. It is also possible to access the settings of the robot through these platforms for example to remotely control the camera or to input room-specific information to ensure comprehensive camera coverage throughout the designated areas.

5. Privacy Protection Measures: The robot is integrated with robust data encryption protocols and privacy features to address concerns related to the recording and storage of personal information, ensuring the user's privacy is maintained.

State-of-the-art

Literature review

Dementia is a syndrome primarily defined by the deterioration of one's cognitive ability beyond what would be expected of biological aging, affecting one's learning and memory, attention, executive function, language, motor perception and social function (Shin, 2022). As a result, this condition can make it difficult, or even impossible, for one with dementia to live independently, often requiring the assistance of a professional caretaker or an informal caretaker (family) in the later stages of the condition. As one would expect, this puts strain on a country's healthcare system, both in terms of personnel and finances; in 2023, the WHO (World Health Organization) estimated that 55 million people worldwide were living with dementia, and they expect this number to nearly triple to 155 million by 2050 (World Health Organization, 2023). The WHO (2023) additionally estimated that the cost of dementia care in 2019 amounted to $1.9 trillion. That is why there is currently a growing demand for robotic caretakers, with a wide range of assistive functionalities, for example, keeping the patient company, reminding them of various tasks, or calling emergency services or other trusted people when the need arises. In 2023, the market for elderly care assistive robots was valued at $2.5 billion, and was projected to grow at a rate of 12.4% to $8.1 billion by 2033 (Saha, 2023).

The increasing aging population faces many challenges, but people with dementia in particular, due to their deteriorating cognitive function, often have difficulties identifying fall risks and can accidentally trip and fall over objects in their home (Canadian Institute for Health Information, n.d., Dementia UK, n.d., Fernando et al., 2017) It is well known that falling is a high danger to elderly people, presenting risk of injury, hospitalization, and can even lead to death. In fact, such accidental falls are one of the leading causes of hospitalization and death in elderly populations (Stinchcombe et al., 2014, Kakara, 2023, Centers for Disease Control and Prevention, n.d.). Moreover, there are challenges involving emergency response coordination, which can lead to delays in the patient being given treatment after falling (Hesselink et al., 2019). Therefore, there is certainly a need to protect elderly people living alone at home from such risks, both via proactive measures involving identifying fall risks and notifying the user (and possibly removing fall risks autonomously, with a sufficiently advanced robot design), but also, by notifying emergency services and the caretaker(s) of the patient if they have fallen and need assistance or hospital care. Since it has been shown that slower EMS responses is associated with increased mortality (Adeyemi et al., 2023), a robot capable of preventing falls would help relieve some of the burden on the healthcare system, caretaker(s), and allow the patient to live more independently.

Naturally, a user-centered approach must be taken when designing solutions, with focus on making the human-computer interaction as user-friendly as possible. In fact, one of the major challenge impeding the large-scale adoption of elderly care social robots into care homes and in cases of independent living is the complexity of many current robots causing more trouble for caregivers and patients rather than relieving them of it; according to Koh (2021), the multiple visual, auditory and tactile interaction of social robots presents challenges and confusion for people with dementia. This makes the focus on user-friendly HCI even more important. Part of this disconnect between the expected and actual relief of burden seems to stem from how current solutions focus on too many things at once and attempt to make a general care robot, rather than specializing in one area. Furthermore, having a complex user interface is a pitfall, as previously discussed, increased complexity creates added confusion for people living with dementia. Despite these pitfalls and challenges, many case studies and state-of-the-art reviews have shown the effectiveness of a variety of elderly care robots (Carros et al., 2020, Raß et al., 2023, D'Onofrio et al., 2017, Søraa et al., 2023, Johnson et al. 2014, Vercelli et al., 2018). Therefore, by identifying the needs of our user and the stakeholders, it should be possible to create a simple-to-use, yet effective, robot that addresses our problem.

Due to gaps in the literature, and the inherent difficulty of this problem, existing solutions can also fall short. For example, Igual et al. (2013) identify several challenges and issues regarding current fall detection systems. Some of the challenges, according to them, include decreased performance in real-life conditions, usability of the system, and a reluctance by its user to accept using it. Furthermore, the issues identified include the limitations of smartphones in smartphone-based detection systems, privacy concerns, difficulty in comparing performance between different systems due to different data-gathering methods, and testability of the system. As such, there are many opportunities for improvement, and our robot should aim to be such an improvement.

Despite the evidence supporting the effectiveness of such robotics in the field of elderly care, papers have also shown its benefits to be overstated. For example, Broekens et al. (2009) showed that although there is some evidence that companion type robots have positive effects in healthcare for elderly people with respect to at least mood, loneliness and social connections with others, the strength of this evidence is limited, due to a variety of factors. However, this mainly applies to companion social robots, which our robot is not. So, we expect that our robot should still provide many benefits to our user group as long as it is designed with them in mind.

As a result of the above, we highlight the need for our proposed solution, because it aims to address some of the challenges and issues that were previously raised, and provides something new that current products do not. With this in mind, we give a brief overview of such current products below, discussing their advantages and, where applicable, where they fall short. We later provide an analysis of our user group, as well as address various ethical concerns that must be taken into account while designing the robot.

Current products

2D-Lidar-Equipped Robot

The LiDAR system continuously scans the environment, creating map of the surroundings. The robot is programmed to recognize the typical shapes and positions of a person standing, sitting, or lying down. If the LiDAR system detects a shape that matches the profile of a person lying on the ground, the robot can interpret this as a person having fallen. The action of the robot is not specified once a fallen person is detected; the paper is more concerned with the detection itself, this was tested in simulations discussed in the paper.

Mobile robot with Microsoft Kinect

The robot includes 3 main components: a Microsoft Kinect sensor, a simple mobile robot, and a PC. The Kinect sensor is mounted on top of the robot and rotates to scan the environment. The sensor data is sent to the connected PC, which processes the information. The PC is programmed to recognize patterns in the sensor data that indicate a person has fallen. This could be based on the shape, position, or movement of the detected objects. If the system detects a fallen person, it sends notifications to a medical expert, authorities, and family members. The main issue with this design is the re-detection of a fallen person, and the difference of detecting a fallen person between different types of robots.

Sensors embedded in the house

The infrared sensors are embedded into the floor throughout the area where fall detection is needed. The system is programmed to recognize the patterns of infrared radiation that indicate a person has fallen. If the system detects a fallen person, it sends a signal to a robot. This robot is equipped with features to assist a fallen person. The robot navigates to the location of the fallen person. It can do this because the system knows which sensors detected the fall, and therefore where the person is located. Once the robot reaches the person, it asks if help is needed. This could be done using a built-in speaker and speech recognition technology. The robot can provide assistance in several ways. by providing the fallen person with a mobile phone or by helping the person stand up using the handles on the robot itself.

Image recognition robots

In this scenario, a LOLA companion robot is repurposed for fall detection. The LOLA robot is originally designed to provide companionship and assistance to people, especially the elderly or those with special needs. A camera is attached to the robot; this allows the robot to visually monitor its environment. The robot uses two algorithms to interpret the images taken by the camera: a Convolutional Neural Network (CNN) and a Support Vector Machine (SVM). The CNN is a type of deep learning algorithm that is especially good at processing images. It can be trained to recognize complex patterns in the images, such as the shape and posture of a human body. The SVM is a type of machine learning algorithm that’s used for classification and regression tasks. In this case, the SVM could be used to classify the output of the CNN. There is no specific reaction of the robot in case a fallen person is detected, the paper was focused on the detection itself.

Wearable Fall Detection Devices

One existing scheme: Apple Watch . If the Apple Watch detects a hard fall, it taps the user on the wrist, sounds an alarm, and displays an alert. The user can choose to contact emergency services or dismiss the alert. If the user's Apple Watch detects that they are moving, it waits for them to respond to the alert and will not automatically call emergency services. After that, if the watch detects that they have been immobile and unresponsive for about a minute, it will call emergency services automatically.

USE analysis

The design of the robot must be taken in coordination with a variety of stakeholders, and not just our target user (who we have defined to be elderly people with mild memory loss due to dementia, living alone at home). Examples of such stakeholders are: formal/professional caregivers, informal caregivers (such as family members), and doctors. Each of these stakeholders have different needs and priorities regarding the care of our target user, and thus, will have different perspectives that will ultimately influence how we design our robot.

Users

Target Group 1: Elderly and Impaired Individuals Living Alone. According to the World Health Organization (WHO), the number of people aged 65 or older is expected to more than double by 2050, reaching 1.6 billion. The number of people aged 80 years or older is growing even faster. From the statistics of Centers for Disease Control and Prevention (CDC), one out of four older adults will fall each year in the United States, making falls a public health concern, particularly among the aging population. Each year, about 36 million falls are reported among older adults each year, resulting in more than 32000 deaths, and one out of every five falls causes an injury, such as broken bones or a head injury.

Needs:

1. In-time fall detection: This is the primary concern for this group. A fall can have serious consequences, and they need a solution that can quickly detect falls and summon help.
2. Ease of use: As this group of people are mainly over 65, learning how to use a complicated product is unrealistic.
3. Automatic running and accurate result: The monitor and call help should be be done automatically and accurately; otherwise, it would give more burden to users and caregivers.
4. Privacy and safety: As this robot needs to monitor the activities of users, they prefer their data will not be stored or stored in somewhere safely. And this robot will not restrict and interfere activities of users.

Target group 2: The caregiver and families. Some family members in developing countries do not have enough time to look after the old because of reasons like severe work overtime; while developed countries are also experiencing the shortage of caregivers. These target groups could be the potential users, as they also expect a method to lighten their burden.

Needs:

1. Reliable assistant: It is stressful and tired for them to keep an eye on the activities on the elderly. Even the professional caregivers cannot focus all their attention on the old, so they prefer a reliable assistant robot to help them while they are doing other things, like preparing medicines. And also the notification from the robot must be reliable, otherwise it wound be another burden for them.
2. Remote monitoring and real-time information: They may want to use the robot to check the situation of the old when emergency happens such that they can take the next step immediately.

Another considerations for users: The product should be cheap enough such that most families can afford it.

Society

As the living standards keep increasing, and more medical resources are publically available, the life expectancy in many countries increases. This results in more aging population in more developed countries. This population needs more care from the public. However, the number of care givers does not meet the need of the aging population. A report shows that by 2030, there will be a shortage of 151000 caregivers in the US . Therefore, governments are interested in investing in automatic care robots, to undertake some responsibilities of caring the elderly.

Needs:

1. Social acceptance: This robot should be socially accepted by the public, so that most elderly will be willing to use this product. Some people might think that installing a robot at home that monitor them every day is not safe and will be an invasion of privacy.
2. Data privacy: The potential problem of data breach should be considered by the government.

Requirements

Design specifications

Index	Description	Priority
1.1	The robot shall have smooth corners.	Must
1.2	The robot shall have a height of at most 1.4 meters.	Must
1.3	The robot shall have a weight of at most 80 kilograms.	Must
1.4	The robot shall be mounted on a base containing at least two wheels.	Must
1.5	The robot shall have a body casing to house its electronics.	Must
1.6	The robot shall be equipped with a camera on its body.	Must
1.7	The robot shall have a rechargeable battery as a power source.	Must
1.8	The robot shall have a screen, microphone and speaker capable of making video calls.	Must

Functionalities

Index	Description	Priority
2.1	When the robot detects a fall, the robot shall notify the designated emergency contact within 1 minute.	Must
2.2	The notification shall be in the form of a VOIP call to the emergency contact, or a SIM-card based call if an Internet connection is unavailable.	Must
2.3	If there is only one emergency contact which has not responded to the call, or if there are two or more emergency contacts and at least two have not responded to the call, the robot shall instead call local emergency services (112, 911, etc.).	Must
2.4	When the robot detects a fall, in addition to 2.2 and 2.3, the robot shall send a text message to the emergency contact.	Should
2.5	The notification (text or call) that the robot sends shall contain the name and location of the user.	Must
2.6	When the robot detects a fall, the robot shall take a picture of the fall and send the picture to the designated emergency contact.	Could
2.7	When the robot detects a fall, the robot shall have a mechanism to allow the user to cancel the notification within 1 minute.	Should
2.8	When the robot detects a fall, the robot shall additionally detect if the user is immobile, and if they are immobile within 5 seconds of the fall detection, it shall send the notification to the emergency contact within 1 second of determining the user is immobile.	Should
2.9	When the robot detects a fall, the robot shall include the location where the user fell with an error radius of at most 10 meters.	Won't
2.10	The robot shall respond to voice commands.	Won't
2.11	The robot shall monitor the user continuously.	Must
2.12	The robot’s battery shall have a battery life of at least 16 hours before needing to recharge.	Must
2.13	All data that the robot processes or sends shall be stored locally on a hard drive.	Must
2.14	When the hard drive reaches 90% capacity, the robot shall delete all previous data recordings.	Must

Safety

Index	Description	Priority
3.1	The robot shall maintain a distance of at most 1.5 meters from the user at all times.	Should
3.2	The robot shall stop moving if it senses a collision with the user could occur.	Could
3.3	During training, the rate of false negative falls shall be at most 1%.	Should

Ethical analysis

The introduction of this home robot designed for safety monitoring, particularly for individuals with limited mobility, raises several ethical considerations that must be carefully addressed. As is mentioned previously in the introduction section, data security is one of the main concerns when it comes to information collecting using cameras and remote data sharing. Other than that, the user (mainly the individuals being monitored) may feel the loss of their full independence and autonomy under monitoring. The introduction of these kinds of robots may also result in people's excessive reliance on technologies, which can potentially reduce their sense of responsibility for their loved ones. The issues and the possible solutions will be discussed as follows:

1. Privacy concerns: The primary ethical concern is related to privacy. The built-in camera program, while essential for safety monitoring, may intrude on the personal privacy of individuals within their homes since it involves the collection and processing of sensitive health-related data. It is crucial to implement robust privacy protection features, ensuring that users have control over camera access and that visual data is securely stored. Clear communication and transparency regarding data usage and storage are essential and the users should be well-informed about every aspect of the technology regarding privacy before opting to use it.

2. Program performance: It is essential for the program to be sufficiently accurate especially when it is dealing with health-related tasks. Any misjudgments or mistakes in decision-making may result in severe consequences. It may raise the problem of accountability and responsibility, as the program developer in this case is supposed to take full responsibility for any unexpected failure of the program. Therefore, the program must undergo strict testing protocols to ensure its precision and reliability.

3. Compromised autonomy: While the robot aims to enhance safety and well-being, the autonomy and privacy of the user are to some extents compromised. Being constantly monitored even by their loved ones has deprived individuals of their personal space. Striking a delicate balance between providing necessary care and preserving personal freedom is paramount. Obtaining consent from individuals before deploying the technology in their homes is crucial.

4. Dependence on technology: With the help from technology, it is no longer necessary for the family members to be physically present most of the time to attend to the user. People's dependence on technology will be more and more significant until they are not taking enough responsibilities for their loved ones. Nevertheless, providing companionship, particularly for elderly individuals, holds equal importance. Moreover, once most of the caretaking jobs have been taken over by technologies, there is a potential risk of human caretakers losing their jobs.

5. Affordability and continuous improvement: It is critical to ensure that the home robot is affordable and accessible to a broad range of individuals. The technology is aimed to solve health-related problems for the entire society rather than the privileged few. The developer hold the responsibility to control the investment on the product and to limit the cost. At the same time, it would be a good practice for the developer to gather feedback and stay responsive. Continuous improvement is desired to address any unforeseen ethical challenges.

Design

Our fall detection system is based on a home robot. A CAD model has been made to demonstrate how the robot might look like. The technical drawings have been generated from the CAD model as shown below.

The robot mainly consists of 3 parts, base, body and a head with screen. The battery will be contained in the base to power the robot. Three wheels are installed at the bottom of the base for movement of the robot. The cameras and the electronics are inside the body. Two cameras together with a small lighting system can be seen at the front side of the body. The head of the robot is mainly a screen that is served as a simple user interface. The user can pick up video calls through the screen.

Approach

In order to reach the objectives, we split the project into 5 stages. The five stages are distributed into 8 weeks with some overlaps. Everyone in the team is responsible for some tasks in these stages.

1. Research stage: In week 1 and 2, we mainly focus on the formulation of problem statements, objectives, and research. We first need to make a plan for the project. The direction of this project is fixed by defining the problem statement and objectives. Doing literature research helps us to gather information of state-of-the-art, the advantages and limitations of current solutions.
2. Requirements stage: From week 2 to week 4 we will do user analysis to further determine the goal and requirements of our product. We will collect information about user needs by surveys and interviews. The surveys and interviews can contain information found in the research stage. For example, how does the user think about the current solution, what improvements can be made.
3. Specification stage: This stage is in week 3 and 4, in which we create the specification of our product using techniques such as UML diagrams and drawing user interface. From the user analysis and the research, we can create the specification in more detail. After this, a test plan will be made so that the product can be tested to see whether it meets the requirements and the specification.
4. Implementation stage: The prototype of our product will be implemented in this stage from week 5 to week 7. We plan to only create the digital part of the product due to time constraints. Also, a more formal test plan will be constructed for later use.
5. Testing stage: In week 7 and 8, the prototype will be tested by the test plan and we can examine whether the product reaches our goal and solves the problem. The finalization on the prototype, presentation and wiki page will be done in this stage.

Planning

We created a plan for the development process of our product based off of the previously described approach. This plan is shown in the Gantt chart below:

A Gantt chart of our development plan.

Task Division

We subdivided the tasks amongst ourselves as follows:

Research			Requirements			Specification			Implementation			Testing
Task	Group member		Task	Group member		Task	Group member		Task	Group member		Task	Group member
Define problem statement and objectives	Everyone		User Analysis	Jie		Create UML Diagrams	Nikola		Implement the prototype	Everyone (TBD)		Test the prototype	Everyone (TBD)
Setup the Wiki page	Yuting		Create Survey	Jie & Feiyang		Define user interface	Samir & Zhiyang		Create formal acceptance test plan	Everyone (TBD)		Work on presentation	Everyone (TBD)
Literature research	Everyone		Analyse Survey	Jie & Feiyang		Make a test plan	Samir		Finalize prototype	Everyone (TBD)
Write Section "Approach"	Yuting		Write Formal Requirements	Everyone
Write Section "Planning"	Samir
Write Introduction	Zhiyang
Write Section "State of the Art"	Samir & Nikola
Perform Stakeholder Analysis	Everyone
Update Wiki	Everyone

Milestones

By the end of Week 1 we should have a solid plan for what we want to make, a brief inventory on the current literature, and a broad overview of the development steps required to make our product.

By the end of Week 3 we should have analysed the needs of our users and stakeholders, formalized these needs as requirements according to the MoSCoW method, and have a clear state-of-the-art.

By the end of Week 4 we should have specified the requirements as UML diagrams, blueprints, etc., created a basic user interface, and created an informal test plan.

By the end of Week 6 we should have created a formal acceptance test plan.

By the end of Week 7 we should have finished the implementation of our product's prototype.

By the end of Week 8 we should have tested the product according to the acceptance test plan, finished the presentation, finalized the prototype, and finalized our report.

Deliverables

The final product will be a robot that is programmed to detect when a user falls and alerts emergency services if they do. Furthermore, we would like it to be capable of identifying fall risks and alerting the user of them, but we do not yet know if this can also be done within the course timeframe.

Logbook

Week 1

Name	Total hours	Tasks
Yuting	6	Introduction lecture (1), meeting (1.5), Approach section (1.5), literature study (2)
Jie	6	Introduction lecture (1), meeting (1.5), Approach section (1.5), literature study (2)
Zhiyang	6	Introduction lecture (1), meeting (1.5), Introduction section (1.5), literature study (2)
Samir	6	Introduction lecture (1), meeting (1.5), Gantt chart (1), Planning section (1.5), Literature research (1)
Feiyang	5	Introduction lecture (1), meeting (1.5), literature study (2.5)
Nikola

Week 2

Name	Total hours	Tasks
Yuting	5.5	Feedback session + meeting (1.5), brainstorming on new ideas (1), Research (2), Analysis of target groups(1)
Jie	7	Feedback session + meeting (1.5), brainstorming on new ideas (1), Analysis of target groups(3), State of the art section(1)
Zhiyang	6.5	Feedback session + meeting (1.5), brainstorming on new ideas (1), rewriting Introduction (2), Ethical analysis section (2)
Samir	10.5	Feedback session + meeting (1.5), brainstorming on new ideas (1), State of the art section (8)
Feiyang	3.5	Feedback session + meeting (1.5), brainstorming on new ideas (1), Analysis of target groups(1)
Nikola

Week 3

Name	Total hours	Tasks
Yuting
Jie
Zhiyang
Samir
Feiyang
Nikola

Week 4

Name	Total hours	Tasks
Yuting
Jie
Zhiyang
Samir
Feiyang
Nikola

Week 5

Name	Total hours	Tasks
Yuting
Jie
Zhiyang
Samir
Feiyang
Nikola

Week 6

Name	Total hours	Tasks
Yuting
Jie
Zhiyang
Samir
Feiyang
Nikola

Week 7

Name	Total hours	Tasks
Yuting
Jie
Zhiyang
Samir
Feiyang
Nikola

Week 8

Name	Total hours	Tasks
Yuting
Jie
Zhiyang
Samir
Feiyang
Nikola

Literature study

1. (Existing product regarding robot that dispensing pills) The robot, managed via an app, securely stores and dispenses medication, provides verbal reminders, and can alert caregivers if doses are missed. It features facial recognition and motion detection to ensure the right person receives the medication. The device complies with patient privacy laws and is positioned as a health care solution amid the growing trend of remote health care technology. Rosen, A. (2019), This robot makes sure you remember to take your pills. CUTTING EDGE | MAGAZINE, available at: https://www.bostonglobe.com/magazine/2019/03/29/this-robot-makes-sure-you-remember-take-your-pills/.
2. (Introducing a new technology and a new way of remote health care) Telemedicine, an emerging technology, enables remote medical consultations through video conferencing or digital imaging systems, fostering coordination and collaboration in diagnosing and treating diseases. A three-tier pervasive telemedicine system utilizes a wireless body area network (WBAN) for continuous healthcare monitoring, with users obtaining vital signals in Tier 1 and transmitting them to healthcare providers in Tier 3 through personal gateways (Tier 2), such as smartphones. Tiers 1 and 2 serve as the client side, providing mobile health (mHealth) services, while Tier 3 represents the server side. Shuwandy, M. L., Zaidan, B. B., Zaidan, A. A., & Albahri, A. S. (2019). Sensor-based mHealth authentication for real-time remote healthcare monitoring system: A multilayer systematic review. Journal of medical systems, 43, 1-30.
3. (Potential challenges raised by telemonitoring technology) Issues include the absence of suitable sensors, concerns about system size and weight, identification of invalid data, battery life, bandwidth, network coverage, and data transmission costs. Adoption challenges are highlighted, such as privacy concerns and potential insurance-related issues. Cultural adjustments in healthcare organizations and the need for new data analysis methods are also mentioned. Nangalia, V., Prytherch, D. R., & Smith, G. B. (2010). Health technology assessment review: Remote monitoring of vital signs-current status and future challenges. Critical Care, 14, 1-8.
4. (Possible design ideas and the drawbacks in remote health-care technology) Several related work and design techniques have been presented. Zhou, B., Wu, K., Lv, P., Wang, J., Chen, G., Ji, B.& Liu, S. (2018). A new remote health-care system based on moving robot intended for the elderly at home. Journal of healthcare engineering, 2018. Available at: https://www.hindawi.com/journals/jhe/2018/4949863/.
5. (Ethical concerns regarding telehealth) The paper discusses challenges related to integrating telehealth into healthcare systems. Concerns about data protection and privacy are raised due to increased access to sensitive patient data. Ethical issues arise regarding patient autonomy and the potential substitution of physical presence in healthcare. Botrugno, C. (2019). Towards an ethics for telehealth. Nursing ethics, 26(2), 357-367.
6. (Collaborative Robot for Remote Dementia Care in Home) This paper shows a teleoperation of a remote care robot at home. This robot is designed for elderly people with dementia. Care givers can use this robot to provide care remotely. They can monitor the patient via robot vision, and control the robot arm via motion tracking. For instance, they can grab medicine and pills for the patient. https://ieeexplore.ieee.org/abstract/document/9116811/authors#authors
7. (Human-Robot Interaction with the Elderly) Some researchers conducted an experiment of replacing a human care giver with a humanoid care robot for 10 weeks. The conclusion is that the elderly are willing to interact with the robot, but they think that the robot cannot replace a human care giver because of techniqual issues, lacking warmth, acceptance, and unexpected situations. https://dl.acm.org/doi/abs/10.1145/3313831.3376402
8. (Patient Monitoring and Medicine Dispenser Robot) This robot is an assistive medical robot for doctors to take care of patients remotely. It combines the pill dispensing and patient monitoring. Doctors can set the prescription for patients. The robot will then remind patients to take pills at required time. It will at the same time recored the patient's temperature via infrared and store it in a database for further analysis. https://pubs.aip.org/aip/acp/article/2494/1/030004/2827068/Patient-monitoring-and-medicine-dispenser-robot
9. (A design of a robotic system to dispense pills) This article introduces the algorithm of a automatic pill dispensing robot. It provides pills to the patient according to a schedule, and remind the patient with sound, light signals and text messages. The signals remain until the patient takes the pills and presses a button. If the patient does not take pills on time, the robot will contact the nurse. https://www.sciencedirect.com/science/article/pii/S0149291817302023
10. (The Role of Healthcare Robots for Older People at Home) This paper discusses problems healthcare robots are facing and what solutions are there. We need to consider the acceptance of healthcare robots by the elderly and privacy issues when designing the robot. The elderly at home can face many different problems. For example, physical problems, mental issues, dimentia and so on. Different robotic solutions need to be considered to solve these problems. https://link.springer.com/article/10.1007/s12369-014-0242-2
11. Robots in elderly care can be used to provide companionship and improve quality of life of elderly people affected with cognitive impairment/dementia, and can assist them in independent everyday living, by monitoring their health and monitoring the environment to detect dangerous situations, like fall risks, and can be used to remind them of medicines, appointments, tasks, etc. Vercelli, A., Rainero, I., Ciferri, L., Boido, M., & Pirri, F. (2018). Robots in elderly care. DigitCult-Scientific Journal on Digital Cultures, 2(2), 37-50. https://digitcult.lim.di.unimi.it/index.php/dc/article/view/54
12. Yang et al. identified 10 grand challenges in robotics in 2018: New materials and fabrication schemes, biohybrid and bioinspired robots, power and energy, robot swarms, navigation and exploration, AI for robotics, brain-computer interfaces, social interaction, medical robotics, and robot ethics and security. Of particular interest to us is: navigation and exploration, AI for robotics, social interaction, and medical robotics. Yang, Guang-Zhong & Bellingham, Jim & Dupont, Pierre & Fischer, Peer & Floridi, Luciano & Full, Robert & Jacobstein, Neil & Kumar, Vijay & McNutt, Marcia & Merrifield, Robert & Nelson, Brad & Scassellati, Brian & Taddeo, Mariarosaria & Taylor, Russell & Veloso, Manuela & Wang, Zhong & Wood, Robert. (2018). The Grand Challenges of Science Robotics. Science Robotics. 3. eaar7650. 10.1126/scirobotics.aar7650.
13. A review of the literature on assistive social robots in elderly care by Broekens, Heerink and Marcel found that there is some evidence that companion type robots have positive effects in healthcare for elderly people with respect to at least mood, loneliness and social connections with others. However, the strength of this evidence is limited, since (a) most studies have been done in Japan, with (b) a limited set of companion robots, i.e., Aibo and Paro, and (c) research designs are not robust enough, usually not described in enough detail to repeat, and confounding causal variables cannot be excluded. However, the review concludes that it is still worthwhile to invest in research methods to better examine the efficacy of social robots in elderly care. Broekens, Joost & Heerink, Marcel & Rosendal, Henk. (2009). Assistive social robots in elderly care: A review. Gerontechnology. 8. 94-103. 10.4017/gt.2009.08.02.002.00.
14. The KSERA (Knowledgeable SErvice Robots for Aging) project integrates smart home technology and a socially-assistive robot to extend independent living for elderly people, in particular those with COPD. The project achieved the goal of integrating smart home technology and socially-assistive robots to allow the extension of independent living for elderly people. The results showed that (1) the KSERA system and Nao robot are likable, (2) the attitude toward the Nao robot is highly correlated with the attitude toward the system, and (3) communication through a robot is preferred over interaction with the individual technical elements of a smart home. Johnson, D.O., Cuijpers, R.H., Juola, J.F. et al. Socially Assistive Robots: A Comprehensive Approach to Extending Independent Living. Int J of Soc Robotics 6, 195–211 (2014). https://doi.org/10.1007/s12369-013-0217-8
15. Direct social robots could decrease loneliness by creating conversational opportunities and, as prior literature (Turkle, 2011) shows, even a sense of attachment, especially as they develop technologically in the future. Additionally, in a study where a humanoid robot Zora was piloted in elder care services, the care personnel noted that, unlike a human caregiver, the robot does not get tired, it always responds in a friendly way, and it repeats things over and over if needed. Furthermore, the robot does not take things personally (Melkas et al., 2020). Breazeal (2004) mentions that one of the advantages of social robots is that they do not have any “social baggage” and therefore do not judge. In addition, it may be less stigmatizing for an older person to receive care from a robot than from a human (Prieto-Flores et al., 2011). Jari Pirhonen, Elisa Tiilikainen, Satu Pekkarinen, Marjut Lemivaara, Helinä Melkas, Can robots tackle late-life loneliness? Scanning of future opportunities and challenges in assisted living facilities, Futures, Volume 124, 2020, https://doi.org/10.1016/j.futures.2020.102640.
16. The use of SARs in mental health research is not yet widespread, new robots and programming are constantly changing, adapting, and expanding. The use of SARs in mental health research and mental health interventions is nascent and has thus far been restricted to specific populations with limited measurement and scope. There is an abundance of opportunity in this area for growth, expansion, and exploration to triangulate SARs usability and efficacy data as the next step in advancing this field. Scoglio A, Reilly E, Gorman J, Drebing C. Use of Social Robots in Mental Health and Well-Being Research: Systematic Review, J Med Internet Res 2019;21(7):e13322. URL: https://www.jmir.org/2019/7/e13322. DOI: 10.2196/13322

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