Patient Monitoring System for Elderly Care using AI Robot

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Patient Monitoring System for Elderly Care using AI Robot
Baby Chithra R
Dept. of Electronics and
Communication
New Horizon College of Engineering
Bangalore,India
chithra.nhce@gmail.com
Salna Joy
Dept. of Electronics and
Communication Engineering
New Horizon College of Engineering,
Bangalore,India
Anju M I
Dept. of Electronics and
Communication Engineering
New Prince Shri Bhavani College of
Engineering
Chennai
Hafifa Namrin
Dept. of Electronics and
Communication Engineering
School of Engineering and Technology,
CMR University
Bangalore,India
Neethu P S
Department of Electronics and
Communication Engineering
School of Engineering and Technology,
CHRIST (Deemed to be university)
Bangalore, India
Abstract— The use of robots in numerous industries has
expanded in recent decades. Self-guiding robots have started to
arise in human life, particularly in sectors pertaining to the lives
of old people. Age-related population growth is accelerating
globally. As a result, there is a rising need for personal care
robots. The purpose of this requirement is to increase
opportunities for mobility and support independence. To meet
this demand, a robot with specific functionalities to help older
people has been designed. The standard values of healthcare
parameters are stored in the database by recording and
comparing the current values the system will give an alarm and
also sends a message to the doctor or caretaker so that a proper
care would be given to the patients. We are including a preset
distance value to monitor the elder people. Here we are using
some sensors to detect the health parameters from the person.
Robot have designed to intimate the family members if any
changes occur in the health parameters. It helps the people to
stay alone in home with safe manner.
Keywords—AI, sensors, Elderly care, Patient Monitoring
System
I. INTRODUCTION
In every technological development the human race
makes, health as a top priority. A recent corona virus outbreak
that partially destroyed China's economy serves as an
illustration of how important health care has grown to be [1-
3]. It is always a better option to monitor the elders using
remote health monitoring technologies in such locations
where the disease is widespread. The current remedy for it is
an Internet of Things (IoT)-based health monitoring system.
More people are developing chronic diseases [4-5]. These
disorders necessitate regular hospital visits for treatment and
monitoring, adding to the workloads of both hospitals and
patients [6-7]. Currently, improvements in communication
protocols and wearable sensors enrich the healthcare system
in a way that will soon transform healthcare services. Of these
developments, remote patient monitoring (RPM) is the most
significant. [1, 8].
As a result, it would be feasible and reasonably priced to
compute visual data that has been acquired by an RGB, depth,
or heat sensor on-site [9-12]. Therefore, it is not necessary to
send the raw data obtained from these kinds of sensors from
inside to the outside [13-17]. As a result, concerns about
privacy, security, and bandwidth shortage shall not exist.
Additionally, real-time computing will be cost-effective for
the aforementioned uses [2, 18-19].
II. RELATED WORKS
In elderly 60 past age, a six weeks robot-assisted, multi-
domain brain programme could increase the effectiveness of
worldwide mental ability and melancholy while mental skills,
that is connected with benefits in remembering power and
other vitals. Like a holistic strategy for enhancing the mental
and physical capabilities of the aged, its RACT programme
should therefore be expanded and continually offered inside
the organizations where people reside [3]. In [3], everything
was discovered how factors like age, ethnicity, or education
level have an impact on how successful an effective training
is. It could be because elderly adults are unfamiliar with using
bots and cell devices. Thus, by combining this learning
alongside formal teaching, it's going to be beneficial to aid the
old in slowly adjusting to it.
The RACT programme might be able to increase folk's
tolerance of intelligent machines, which is an intriguing
strategy for reducing that exists with seniors. This degree of a
user's mental ability and long course results ought to be the
center of future studies as well as the creation of a customized
programme. The Fig.1. depicts the model that is employed for
the analysis in [3].
Fig.1. Experimental setup in [3].
2022 6th International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS) | 978-1-6654-5699-9/22/$31.00 ©2022 IEEE | DOI: 10.1109/CSITSS57437.2022.10026384
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This team made utilization of the controlled robotic Sil-bot .
Inside the machine class, users replied to commands that used
a wearable tracking pad, with the exception of three
programme when the robotics observed and assessed the users'
movement. Users received instruction from experts on how to
operate the robotic for psychological treatment. The key
responsibilities of the teachers inside the robotics program
included helping members choose programme and, when
appropriate, providing or repeating commands. In contrast
towards the TCT, the RACT incentivized respondents by
providing personalized response for every issue as soon as
they entered a response on their connected phones. However,
at time, results were recorded. 22 perceptual education
programs have been utilized in sum again for RACT, such as
6 programmes for recollection, 3 programme for density, 2
programme for focus and cognition, 1 programme for density
and visual recognition, 2 for logic and decision, 1 programme
for visual understanding, 1 programme for dialect, 1
programme for computation, 1 programme for estimation and
ability to focus, 2 programme for visuospatial feature, and 2
programme for strength training. Relying on HRI technology,
this bot can exhibit a range of expressions and feelings. It is
also able extend its arms, shoulders, and neck, as well as travel
in any manner using its down tire. Since it is a robot and is
well-known to its owners, the reported bot can discern their
intentions, looks, and facial reactions. Additionally, it is able
to drive itself. This bot with cutting-edge intelligence, can
indeed be operated by non-experts, therefore it was utilised as
an auxiliary teacher in the report's cognition-improving
programme.
Even while emotional technology is evolving, obstacles still
stand in the way of medical bots having able to communicate
with empathy. To give elderly people with disease the best
care possible today, it's critical to recognize, articulate, and
solve these problems. One goal of [4] was to investigate the
difficulties medical bots face in communicating to dementia-
stricken aged folks. Elevated cameras were used in an
exploratory nature study involving the Spice robotic and
elderly individuals with Alzheimer to record main
communication events that took place even during events. The
information was gathered on December 2020.
Tanioka's group and the Xing Corporation worked together to
create the app for just an intended dialogue utilizing Pepper,
which enables controller of Pepper's utterances and body
motions. These same outcomes study identified four issues:
(1) precise detecting behavior for "having to listen" to
speakers suitably and precisely conversing to topics; (2)
ineptitude throughout "having listened" and "stare" actions;
(3) truthfulness of behavior; and (4) insufficiency in human
language needed to process Ai, i.e., this same capacity to
vigorously respond to circumstances that weren't pre-
programmed by builder. This robot's interactions to
individuals with dementia during conversations demonstrated
a useful application of AI and NLP technologies. To improve
the possibility of empathetic dialogue between medical robots
and elderly people with illness, the growth concerns
discovered in this study must be resolved. Whilst COVID-19
visitation restrictions were put in place to save inhabitants,
they simultaneously posed the danger of worsening that social
and emotional solitude which occurred amongst older people
prior towards the epidemic. the work in [5] outlines a study
that used bots and online interactions to keep the online
platforms of senior patients and care home inmates,
accordingly, in order to alleviate sadness as well as social
withdrawal in care homes. Participants inside the prospective
study have been either geriatric patients or inhabitants of care
homes. Every participant was required to complete a survey
with three structured questions to gauge their level of isolation
[6]. The survey additionally noted if visual communication
using the bot, a different method of communication (such as a
telephone conversation), or even no communication involving
family members has occurred. Its purpose was to determine
general support as well as the advantages for online
interactions utilizing bots in multiple positions. Inside this
research, 70 participants were exposed to one of 3 potential
initiatives: zero interaction; simulated contacts with a bot; or
any additional touch. And over duration of the study, its bot
was utilized more frequently, and even during the weeks when
visitors were prohibited, this one was frequently employed
throughout all venues.
Based on the information gained from our extensive welfare
mobile robots, the research in [6] presents for creating a senior
care basis for social engagement including physical and
intellectual stimulus. This piece presents the initial findings
of better functionality of the system. This system can provide
the individual a wide range of services like data,
entertainment, gaming, workouts, and songs. Using the
questions from the mini-mental examinees, the videogame’s
bi-modal interaction of voice and touchpad have already been
developed to stimulate human brain. Clinicians may examine
a person's performance via a graphical interface, which
already enables doctors to create unique treatment
programmes for every client, or store the findings in a public
cloud. The system has undergone testing and validation, with
first human volunteers followed by a bot which has been
operating in a geriatric care home for such a considerable
amount of time. Findings & comments indicate that perhaps
the bot may maintain sensing capabilities both
psychologically and physically while also maintaining their
cognitive and physical activity.
AI have made significant growth in the last decade, and now
they have the ability to improve the medical industry.
Mechanical systems are regularly used in clinics, for mobility
aid and retraining, as well as in treatment of the elderly,
infants, or disabled people. The latest events in automation
systems used in the medical industry were covered in this
questionnaire [7]. In-depth details on cutting-edge work in
healthcare, nursing, helpful, therapy, or mobility helping bots
were provided in this work. These outstanding problems that
medical bots must overcome to become a component of
society are indeed covered in the study.
The COVID-19 epidemic has exerted a significant negative
influence on everyone's well-being and safety, particularly
older people's safety. In order to lessen the impacts, such as
solitude, as well as to lighten this burden across both
professional and unofficial caretakers, assistive robot was
developed. The report provides the first comprehensive
analysis and assessment as to how emotionally helpful
computers had especially aided this community, in addition to
an overview of these robots' health impacts generally and their
adoption throughout the epidemic. The purpose of [8] is to
provide responses to research questions concerning the types
of SARs utilized even during epidemic, the activities that was
employed on, as well as the factors that facilitated and
hindered their usage. They will additionally go through the
insights that can be learnt through its use to improve SAR
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conception and implementation in the future as broaden its
applicability and acceptance in a post-pandemic era.
III. PROPOSED SYSTEM
This paper discusses the various parameters through which
the health can be monitored especially for the elderly people.
A. Methodology
In this system four sensors are used which can be placed
at appropriae spaces in order to monitor the heart rate, SPO2,
temperature and fall stutaus of the patient or elderly people.
The four sensor modules are heartbeat sensor, LM35
temperature sensor, SPO2 sensor and ultrasonic sensor. Fig.1.
shows the block diagram of the proposed system in which the
four sensor units are integrated to the arduino nano
microcontroller. The data is being analysed and stored in the
cloud which can be accessed by the doctor whenever its
required.
Fig.2.. Block Diagram of Proposed system
Fig.3. Block Diagram of AI system used in this work
B. Working
A very fundamental optoelectronics principle governs how
heartbeat sensors function. A pair of LEDs, an LDR, and a
microcontroller are all that are required to measure your heart
rate. The surface of an IR led reflects the infrared light that it
generates. Depending on the surface's reflectivity, the amount
of light reflected varies. When this reflected light strikes an
IR sensor that has been reverse biassed, reverse leakage
current results. The quantity of electron-hole pairs produced
varies with the strength of the incident IR radiation. Thus the
heartbeat is calculated and continuously monitored. A
moving average model is developed and a heartrate average
for a duration of 2min change is recorded.
The oxymeter is placed on the patient’s finger and the
SPO2 level is monitored continuously and the MCU node
acts as a gateway to the internet. The Zigbee module supports
the Node MCU ESP32 for processing the sensor readings.
Precision integrated-circuit temperature sensors from the
LM35 series have an output voltage that is linearly relative to
the temperature in Celsius.
An ultrasonic sensor is connected in the vehicle which not
only follows the patient who makes simple to and from
movements it also confirms the fall status of the patient.
An AI model is developed by making use of CNN
algorithm to classify the status of the patient and giving alert
and sending messages to the caretaker as depicted in Fig.3.
The Caretaker can also view the previous history of the
measured parameters of the Patient or elderly people and start
the treatment or medications accordingly.
IV. RESULTS
Fig. 4 illustrates the physical model and Fig5 the output model
of suggested AI Robot. The robot is capable of identifying the
patients' health parameters. It uses a variety of sensors to
detect the temperature, heartbeat, oxygen level, and falls. The
output model Robot can track patient movement through
ultrasonic sensor. Family members will continuously receive
the info from this device.
Fig. 4. Physical model of AI Robot
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Fig. 5. Output model of monitoring Unit
Fig. 6. Output model of Parameter Display
The Heart Rate, SPO2, Temperature and fall status are
monitored as shown in Fig. 6. The history of the patient or
elderly person can be analyzed from the chart shown in Fig.7.
The AI model sends the data to the Doctor or caretaker. When
there is a difference in the parameters’ values are deviated
from the prescribed values as compared to the standard values
that stored in the database then the system will alert the care
taker or doctor.
Fig. 7. Output model of Parameter Display
V. CONCLUSION
This suggested system features AI robot that is useful
for older persons. This robot has a servo motor and a node
MCU to control its movement. A clip is attached to the
patient's index finger, and many sensors are built inside it to
monitor vital signs. The main goal of this work is to keep a
specified distance between the patient and the robot while
monitoring their vital signs. If the patient's physical state
changes, a message is sent to their loved ones. This work can
be extended in future by developing a mobile app through
which the health parameters of the elderly person can be
checked as on when required. Also, as a part of health
monitoring, the regular medicine and the medicine required
for the patient based on the current health parameters can be
dispensed to the Patient’s reach.
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