The 2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)Developing a Platform of Personalized
Conversation Scenarios for In-home Care
Assistance
Sinan Chen 1 , Masahide Nakamura 1,2 , Sachio Saiki 3
1Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada, Kobe, 657-8501, Japan
2
RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo, 103-0027, Japan3
Department of Data & Innovation, Kochi University of Technology,
185 Miyanigutu, Tosayamada-cho, Kami-shi, Kochi, 782-8502, Japan
Email: chensinan@ws.cs.kobe-u.ac.jp, masa-n@cs.kobe-u.ac.jp, saiki.sachio@kochi-tech.ac.jp

Abstract—The burden on family caregivers for in-home careis increasing in a super-aging society. Realizing conversational
agents adapted to individual situations for in-home care assistance is a hard technical issue. The purpose of this paper is torealize a method that can create a personalized conversational
agent by the end-user. The challenging points of this paper
include two aspects: (1) Editing conversation scenarios easier for
end-users. (2) Sharing edited conversation scenarios with others.
As the approach, we ﬁrst present a platform of personalized
conversation scenario (PoPCS). Then, we create a logs-asscenarios concept to improve the personalized contents and theedited efﬁciency. By selectively sharing the conversation logs, webuild a connection between the local conversational agent andthe remote that seems like telemedicine. Since different family
caregivers and healthcare specialists join in it, continuing to
improve the conversation scenarios for in-home care assistanceis promising.
Index Terms—in-home care assistance, conversational agents,
scenarios, end-user, web service

I. I NTRODUCTION
With the global aging of the population, the number ofpeople requiring nursing care is increasing year by year. At
the same time, as the demand for nursing care in a superaging society is increasing, the population, social, and disease
structure are changing. A shortage of medical, institutions
and the staff of nursing care is becoming a social situation.
Though policies in Japan 1 have been formulated to switchfrom institutional care to in-home care, the burden on
family caregivers has been increasing. Our research grouphas been studying various conversational agents for in-homecare assistance in a super-aging society, including operation
assistance for the home appliance [1], memory assistance forthe elderly people [2], and daily counseling for people withdementia [3]. However, a hard part of the current technicalissues is how to realize conversational agents adapted toindividual situations for in-home care assistance. Due to ahuge difference among users’ needs exist, it is unrealistic tobuild a unique conversational agent by developers from one
household to another.

The goal of this paper is to realize a method that can createa personalized conversational agent by the end-user for inhome care assistance. To achieve the goal, we are currently
developing a platform of personal conversation scenarios(PoPCS). More speciﬁcally, the PoPCS is a web-based platform that can not only edit and share conversation scenarios
by family caregivers but also execute edited conversation
scenarios as a virtual caregiver for the individual in-homecare assistance. As the approach, we ﬁrst deﬁne three roles:
care recipients, family caregivers, and healthcare specialists.
Next, we focus on the conversation logs and scenarios, todesign three main function modules for the local and remoteconversation agent, including conversation logs, scenario editors, and conversation models. Then, we produce a complete
description for each function module. Our key idea is alogs-as-scenarios concept that not only uses conversation
logs as references of scenarios by family caregivers but also
selectively shared to the healthcare specialists and others forchecking and referring. Compared with traditional ways (e.g.,going to the institution or making a call respectively), it cansave time, money, and manpower, when some of the carenursing problems are encountered at home.
As a case study, we discuss the three directions for inhome care assistance using the PoPCS, including mental
healthcare, medication reminder, and worries or problems
response. Moreover, the advantages and the limitations of the
PoPCS are also discussed by us, to determine the directions
in future work.
II. P RELIMINARIES
A. Problems in Super-aging Society
In recent years, population aging is increasing worldwide,
especially problems in super-aging society. A super-aging
society refers to a society in which the proportion of the
population aged 65 and over (aging rate) accounts for 21%of the total population [4]. Looking at the ranking of theworld’s aging rate 2 , developed countries tend to be higher,
and developing countries tend to be lower. Regarding the1 https://www.mhlw.go.jp/seisakunitsuite/bunya/kenkou iryou/iryou/zaitaku/
dl/zaitakuiryou all.pdf (in Japanese)978-1-6654-4494-1/21/$31.00 ©2021 IEEE148

2 https://population.un.org/wpp/Download/Standard/Population/

The 2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)

top three countries with aging rates, Japan is 28.7%, Italyis 23.3%, and Germany is 21.7%. In addition, when viewed
from the whole, one in 11 of the world’s population at thetime of 2019 (9%) is greater than or equal to 65 years ofage. There is a prediction that the proportion will increase to
one in six people in 2050 (16%). Against this background,the population, society, and disease structure are changing invarious countries around the world, and the number of people
requiring nursing care is increasing year by year.
B. Burden on Family Caregivers for In-home CareWith the demand for nursing care increasing in a superaging society, the related problems have to be faced, suchas a shortage of medical and welfare institutions, a staff
shortage in the nursing care industry. In order to improvethese problems, and realize people their own lives who
require nursing care, policies in Japan have been formulated
to promote cooperation between nursing care facilities andswitch from institutional care to in-home care. As the caseof in-home care, while people who require nursing care arepossible to continue living in a familiar home, a mental andphysical burden on family caregivers has been increasing.
A variety of problems related to in-home care, like fulltime care for 24 hours due to serious illness, an older adultcaring for even older parents, an elderly couple with dementia
but nursing care of each other, and the elderly living alone
are becoming prevalent. Research on assistive technology
is progressing all over the world, which attempts to solvethese problems of home care through cooperation between
machines and humans.
C. In-home Monitoring System Using an Agent Concept
The typical system for in-home care assistance is an “inhome monitoring system” for people requiring nursing care,using ICT, Internet of Things (IoT), Artiﬁcial Intelligence(AI), cloud technologies, robots, and so on. The key ideaof it is an agent concept that uses the machine to replace family caregivers, to make an interaction with people
requiring nursing care at home. One way by introducing
sensors into the home, to achieve a variety of effects likerecording the status of sleeping [5], estimating the excretion[6], and fall prevention [7]. Other ways have been actively
developing, such as using a camera device, the research[8] on the measurement of physical activity for long-term
in-home nursing care is proposed by us. Moreover, at any
time of day or night, the machine will let family caregivers
know promptly when all kinds of timing or signals requiring
nursing care are coming, like toilet assistance, medication
reminder, and assistance in changing physical postures. Using
this approach, reducing the burden of family caregivers andimproving the Quality of Life (QoL) of people requiring
nursing care is promising.

E. Existing Cloud Platforms and Challenging Points
Rapid progress in cloud technology has made many cloud
platforms for conversational agent services continue to appear, such as Google Cloud Dialogﬂow 6 , Microsoft Bot
Framework 7 , Amazon Alexa Skills Kit 8 , and IBM Watson
Assistant 9 . Using cloud computing and resources, highperformance processing (e.g., Natural Language Processing(NLP), etc.) can be moved from edge devices to the cloud,to achieve high-quality conversational agent services. On the
one hand, cloud platforms can be associated with their smart
products (e.g., smart speakers, smart watches, etc.) that allow
users to edit scenarios of conversational agents for a special
purpose. On the other hand, the various functions of cloud
platforms are open to developers as cloud services, which
can be used to associate other devices and services, so as toachieve more effects through more ﬂexible utilization. However, we consider that challenging points of these platforms
are how to be conveniently used by end-users rather thandevelopers. For special purposes like in-home care assistance,a huge difference among users’ needs exists. It is unrealistic
to require all users to use smart products, or build a unique
agent by developers from one household to another.
F. Requirements of Conversation Scenarios for End-users
Realizing conversational agents adapted to individual situations for in-home care assistance is a hard part of the current
technical issues. Except for some speciﬁc smart products, inthe conversational agent systems for in-home care assistance,
most of the conversation scenarios and services are based
3 https://www.vstone.co.jp/products/sota/ (in Japanese)
4 https://www.medical-switch.com/ (in Japanese)

D. Existing Conversational Agents and Related Work
Using the form of conversation to interact between people
requiring nursing care at home and the machine that is calleda conversational agent is one of the topic issues for in-homecare assistance. The interaction approach of conversational

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agents often includes two ways: text-based and speech-based.
Regarding text-based conversational agents, they rely on text
input from users, where the related work includes mobilebased “chatbot” service using Line Application Programing
Interface (API) [9] and a rule-based “mind” sensing service
integrating with MPAgent [10] have been widely deploying.
However, there are also some elderly people who do notunderstand the method of text input and feel inconvenient. By
contrast, speech-based conversational agents with two types
including robot and virtual User Interface (UI) have been
more popular among the elderly. A variety of speech-based
nursing robot products have been introduced into generalhouseholds that functions include information presentation
3, medication reminder 4 , safety conﬁrmation 5 , and soon. Our research group has been studying speech-based
conversational agents with virtual UI, like speciﬁc softwareor web applications. In previous studies, operation assistancefor the home appliance [1], memory assistance for the elderly
people [2], and daily counseling for people with dementia [3]have been proposed.

5 https://www.necplatforms.co.jp/solution/papero i/index.html(in Japanese)
6 https://cloud.google.com/dialogﬂow?hl=en
7 https://dev.botframework.com/
8 https://developer.amazon.com/en-US/alexa/alexa-skills-kit
9 https://www.ibm.com/cloud/watson-assistant149

The 2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)TABLE I
E ND - USERS AND APPLICABLE CONDITIONS IN THE P O PCS

End-users

Local
Virtual Caregiver

Applicable Conditions

Conversation
logs(1) Have professional knowledge

Scenario
editors

Healthcare specialists to solve problems of home care.
(2) Have the basic ability of theCarerecipients

web operations of PC or mobile.
(1) Have worries or problems in
Family caregivers

Conversation
model

Familycaregivers

the process of performing care.
Fig. 1. Use case diagram for a local virtual caregiver.

(2) Have the basic ability of the
web operations of PC or mobile.

RemoteVirtual Caregiver(1) Have worries or problems in
Care recipientsthe process of requiring care.

Conversation
logs(2) Have the basic ability tocommunicate in any language.

Scenario
editors
Familycaregiverson the deﬁnition of the developer rather than the end-user.
Hence, we consider that there are two potential requirements
for end-users as follows:
R1: Editing Conversation Scenarios Easier for End-users
End-users can edit conversation scenarios to suit the conditions of people requiring nursing care, like habits andinterests.
R2: Sharing Edited Conversation Scenarios with Others
End-users can share edited conversation scenarios with theother communities and regions, as references for others.
The long-term vision of our study is to realize a platformof conversational agents for in-home care assistance that endusers can edit, perform, and share the conversation scenarios.

Conversation
model

Healthcare
specialists

Fig. 2. Use case diagram for a remote virtual caregiver.

III. P O PCS: P LATFORM OF P ERSONALIZEDC ONVERSATION S CENARIOS
A. Outline
To improve the requirements described in Section II-F, weare currently developing a platform of personalized conversation scenarios (PoPCS) for in-home care assistance. The
ideal image of the PoPCS includes the following two aspects:(1) Can edit and share conversation scenarios from the webbrowser of various devices, like computers, tablets, and smart
phones. (2) Can execute edited conversation scenarios asa virtual caregiver by the web browser for the individual
in-home care assistance. For this, as the approach, we ﬁrst
identify the required function modules in the PoPCS. Then,
we produce a complete description for each function module.
End-users and applicable conditions are shown in Table I.
B. Function Modules
To determine end-users in the PoPCS, we deﬁne threeroles: care recipients, family caregivers, and healthcare specialists. Figure 1 and 2 respectively depict the use case978-1-6654-4494-1/21/$31.00 ©2021 IEEE

Fig. 3. Conceptual diagram of overall architecture in the PoPCS.

diagram for a virtual caregiver in the local and remoteenvironment. The virtual caregiver here means a speechbased conversational agent using the web browser, which
can realize a variety of in-home care assistance, such as
mental healthcare, medication reminder, as well as worries orproblems response. For each virtual caregiver, we deﬁne threemain function modules: conversation logs, scenario editors,
and conversation models. The conceptual diagram of overallarchitecture is shown in Figure 3. The key idea of the PoPCS
is a logs-as-scenarios concept. The conversation logs are not
only re-used as scenarios by family caregivers in the edge
device, but also selectively shared to the cloud database, forchecking by healthcare specialists and referring with others.

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The 2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)Fig. 5. Examples of form-based and ﬂow-based scenarios.

D. Module 2: Scenario Editors

Fig. 4. Internal structure diagram of the function modules.

Figure 4 shows a internal structure diagram of the function
modules. More speciﬁcally, the description of each function
module consists as follows.

C. Module 1: Conversation Logs
Module 1-1: Local Conversation Logs
Using the web speech API [11], automatic speech recognitionand synthesis can be easily realized in the web browser.
We design two kinds of location conversation logs in the
PoPCS: human-to-human conversation logs, human-toagent conversation logs. In the human-to-human conversation
logs, conversation voices around the local virtual caregiverare automatically converted to text and saved in the edge
device. In the human-to-agent conversation logs, the agent
here equals a virtual caregiver. To distinguish it from humanto-human conversation logs, end-users can create a name of
the agent that is regarded as a keyword for waking the virtual
caregiver to talk with the person. In this way, the human-toagent conversation can be realized and recorded by callingthe name of the agent every time. The methods of generating
local databases in the web browser include Appcache [12],IndexedDB [13], WebSQL [14], and File System API [15].
Module 1-2: Remote Conversation Logs
The remote conversation here means the humans-to-agent
conversation using the web browser connected to the internet.
We design two kinds of remote conversation logs in the
PoPCS: humans-to-agent conversation logs, the shared local
conversation logs. In humans-to-agent conversation logs, apublic virtual caregiver talks with family caregivers fromdifferent households that the conversation logs in the text areautomatically saved in the cloud database. As for the shared
local conversation logs, family caregivers can selectively
share the local conversation logs to the cloud database, forchecking by healthcare specialists or referring with others.
Remote conversation logs are not only public to each family
caregiver, but also re-used as public scenarios by healthcare
specialists. The methods for building remote databases in
the cloud server include MongoDB [16], MySQL [17],PostgreSQL [18], and Microsoft Access [19].

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Module 2-1: Task-oriented Scenario Editor
The key step for executing conversation models is to edit
scenarios, which directly affect the quality, sustainability,and purpose of the human-to-agent conversation. The taskoriented scenario editor means editing the required scenarios
for a special purpose, like event reminders and personal
concerns extraction, where the conversation initiator is theagent. Speciﬁcally, it often can edit two kinds of conversation
scenarios: form-based scenarios, ﬂow-based scenarios. Figure
5 shows examples of form-based and ﬂow-based scenarios.
Using the task-oriented scenario editor, family caregivers
can freely edit and update for building conversation models.
However, it is not fully convenient because it needs hugemanual input for many complex scenarios. For this, weconsider that a variety of conversation logs can be used
as references to scenarios. In a word, a logs-as-scenarios
concept is produced by us. Compared with the task-oriented
scenarios, the advantage of the concept further concentrates
on the non-task-oriented.
Module 2-2: Non-task-oriented Scenario Editor
The non-task-oriented scenario editor means editing conversation scenarios that possibly appear on the care recipient.
Unlike the task-oriented scenarios, it is full of uncertainty andrandomness, because the conversation initiator is the humanrather than the agent. Hence, for editing non-task-oriented
scenarios that can ﬁt the personality, the logs-as-scenarios
concept is of great signiﬁcance. Speciﬁcally, we ﬁrst deﬁne
attributes for each kind of conversation scenario. Referring
to Figure 5, attributes in form-based scenarios often include
keys (in the left column) and values (in the right column).
And attributes in ﬂow-based scenarios often include questions, options, as well as answers. The approach for buildingclassiﬁers includes document similarity measures [20] andmorphological analysis [21]. Family caregivers can manually
select the related logs from different attribute groups, to build
relationships for the non-task-oriented scenarios.
Module 2-3: Remote Scenario Editors
Remote scenario editors mean deploying the above twokinds of scenario editors to the cloud server. Unlike thelocal scenario editors, the remote scenario editor corresponds
to the above Module 1-2, in order to ﬁnd problems andcreate answers in scenarios by healthcare specialists fromremote conversation logs. As a part of the remote virtual151

The 2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)

caregiver, the remote scenarios are public for every local
family caregiver. Compared with traditional ways (e.g., goingto the institution or making a call respectively), it can savetime, money, and manpower, when some of the care nursing
problems are encountered at home. Moreover, for the sameproblem included in the conversation logs, the corresponding
answers can be made by multiple healthcare specialists fromdifferent views at the same time. The popularity of every
remote conversation scenario can also be public and referring
to others. In this way, continuing to improve the shared
database for in-home care assistance in the form of virtual
conversation is promising.
E. Module 3: Conversation Models
Module 3-1: Local Conversation Model
The local conversation model means a virtual caregiver athome, by executing the edited conversation scenarios that
directly face the care recipient. It includes three modes:
continuous listen mode, active conversation mode, and passive conversation mode. The continuous listen mode aims tocollect human-to-human conversation logs (refer to Module1-1). In the active conversation mode, the agent is a conversation initiator that aims to remind events or extract personal
concerns of the care recipient in the form of conversation(refer to Module 2-1). As for the passive mode, the carerecipient is a conversation initiator where the answer by theagent will use the non-task-oriented scenarios (refer to Module 2-2). Of course, the contents of exceptional conversation
exist. For this, they require adding the answer by family
caregivers, or sharing to the remote layer to wait for theanswer from healthcare specialists. The method of the abovemodes switching is calling the keyword created by family
caregivers, which is similar to the description of naming theagent in Module 1-1.
Module 3-2: Remote Conversation Model
The remote conversation model means a virtual caregiver
deployed in the cloud server, by executing the edited scenarios that face all family caregivers when any required.
Corresponding to the above Module 1-2 and 2-3, the remoteconversation model offers a humans-to-agent conversation in
the cloud layer. It just has a passive conversation mode but
can talk with multiple family caregivers in turns. Moreover,unlike the local conversation model, due to a part of theremote scenarios based on the shared conversation logs
and the answers from healthcare specialists, the common
problems in the process of in-home care will be collected
and answered more intensively by the remote conversation
model. In this way, building the connection between different
family caregivers and institutions, we believe that it can not
only reduce the stress of family caregivers but also improve
the quality of life (QOL) of the care recipient at home.

In order to reduce the mental fatigue and stress of family
caregivers, the psychological state of the caregiver is common
to be grasped from the questionnaire survey of depressive
symptoms [22] and care burden [23] in the mental healthindex. However, there is a troublesome aspect of reading andchoosing questionnaires on a regular basis. This may add afeeling of further fatigue for family caregivers. Therefore,
we consider that can regard the contents of questionnaires
as task-oriented scenarios in the PoPCS. In this way, thepsychological state can be expected to be measured in arelaxing process, through speech-based conversation between
the family caregiver and the agent. Compared to the written
language, the interview questionnaire [24] is easier to use
for conversation scenarios. Hence, in order to achieve theexpression of daily conversation, it is a challenging point todevise the oral language of the questionnaire.
B. Medication Reminder
In order to prevent care recipients from forgetting totake medication, applications, software, and nursing carerobots have been used to improve medication management
for the care recipients. However, there are usability andcost problems, due to requiring installing applications orpurchasing robot equipment. Therefore, we consider that canregard the contents of the medication time and information
as task-oriented scenarios in the PoPCS. In this way, family
caregivers can grasp the status of the medication reminder bychecking the conversation logs of the care recipient. Moreover, using human-to-agent conversation logs, the experienceof taking the medicine can also be shared with healthcare
specialists and others, which is signiﬁcance for long-term
nursing care.
C. Worries or Problems Response
There are often different worries or problems for every inhome care site, such as a decrease in the quality of life (QoL)
at home, unknown nursing care measures. Generally, family
caregivers take measures by referring to the opinions ofexperts through the care consultation desk or home-visit careservices. However, the sharing of related problems amonghouseholds is ﬁnite, and the information obtained from the
web is not concentrated. For this, we consider that can regard
worries or problems as non-task-oriented scenarios to beshared in the PoPCS. Healthcare specialists will respond ina uniﬁed manner to similar problems that the local virtual
caregiver in each household cannot answer. In this way,
worries or problems will efﬁciently respond by the remotevirtual caregiver.
V. D ISCUSSION
A. Advantage

IV. C ASE S TUDY
In this section, as a case study, we explore using the
PoPCS to realize personalized in-home care assistance inmore detail. Speciﬁcally, we discuss the three directionsof in-home care assistance: mental healthcare, medication
reminder, and worries or problems response.

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A. Mental Healthcare

In this paper, we consider that the advantage of the PoPCS
includes the following two points:• Improvement of equipment and software used:
It does not require mechanical robots or software installation, and can be easily used with the web browser.

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Improvement of ﬂexibility in editing scenarios:
A variety of conversation scenarios for end-users can be
developed on the web UI and personally adapted.
In this way, it can be expected that the editing andoperation of conversational agents will become easier andmore diversiﬁed to in-home care assistance.
•

B. Limitation
As for the limitation of the PoPS in this paper, we consider
that it includes two points as follows:• Scalability issue:
In some cases, just a speech-based conversational agent
is not sufﬁcient to support long-term nursing care athome. For example, the scalability for using environmental data and image data together is indispensable
for special needs such as fall prevention for the elderly.
• Privacy and security issues:
Traditionally, privacy and security issues have been technology development and service application. In manycases, there was a trade-off relationship. The privacy
and security protection of the shared text data in this
proposal also requires to be considered.
VI. C ONCLUSION
In this paper, a method that can create a personalized
conversational agent for in-home care assistance has beenpresented by us. To achieve the method for end-users, we
described a platform of personalized conversation scenarios(PoPCS) and analyzed the function modules. We also discussed the case study in three directions of in-home careassistance using the PoPCS. As future work, we should
develop an automatic algorithm for the logs-as-scenarios
concept in the PoPCS. Also, we are planning to evaluate thefunction module limitations in practical scenes (e.g., emotion estimation from conversation logs [25]). Investigating
the characteristics of personality to improve the ﬂuency ofhuman-to-agent conversation is also an interesting challenge.
ACKNOWLEDGMENT
This research was partially supported by JSPS KAKENHI
Grant Numbers JP19H01138, JP18H03242, JP18H03342,
JP19H04154, JP19K02973, JP20K11059, JP20H04014,
JP20H05706 and Tateishi Science and Technology
Foundation (C) (No.2207004).
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