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Version 62.1 by Vishruty Mittal on 2022/04/02 12:27

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Vishruty Mittal 57.1 1 Evaluation is an iterative process where the initial iterations focus on examining if the proposed idea is working as intended. Therefore, we want to first understand how realistic and convincing the provided dialogues and suggested activities are, and would they be able to prevent people from wandering. To examine this, we conduct a small pilot study with students, who role-play having dementia. We then observe their interaction with Pepper to examine the effectiveness of our dialog flow in preventing people from wandering.
Clara Stiller 2.4 2
Clara Stiller 2.5 3
Xin Wan 1.2 4 = Problem statement and research questions =
Clara Stiller 4.1 5
Simran  Karnani 1.4 6 **Goal**: How effective is music and dialogue in preventing people with dementia from wandering?
Bart Vastenhouw 1.1 7
Clara Stiller 2.7 8 **Research Questions (RQ):**
Simran  Karnani 10.4 9
Simran  Karnani 1.4 10
Simran  Karnani 10.3 11 1. What percentage of people are prevented from going out unsupervised? (Quantitative) (CL01, CL05)
Simran  Karnani 10.5 12 1. How does the interaction change the participant's mood? (CL02)
Clara Stiller 40.1 13 1. Can the robot respond appropriately to the participant's intention? (CL03)
Simran  Karnani 10.5 14 1. How do the participants react to the music? (CL04)
15 1. Does the activity that the robot suggests prevent people from wandering/ leaving? (CL06)
Simran  Karnani 13.1 16 1. Can pepper identify and catch the attention of the PwD?
Simran  Karnani 1.4 17
Clara Stiller 40.1 18 //Future research questions//
Simran  Karnani 10.4 19
Simran  Karnani 14.1 20 1. Does the interaction with Pepper make PwD come back to reality? (CL08)
21 1. Does the interaction with Pepper make PwD feel he/she is losing freedom? (CL09)
22 1. Does preventing the participant from going out alone make them feel dependent? (CL10)
Vishruty Mittal 9.1 23
Xin Wan 1.2 24 = Method =
Clara Stiller 4.1 25
Vishruty Mittal 61.1 26 A between-subject study with students who play the role of having dementia. Data will be collected with a questionnaire that participants fill out before and after interacting with Pepper. The questionnaire captures different aspects of the conversation along with their mood before and after the interaction with Pepper.
Bart Vastenhouw 1.1 27
Vishruty Mittal 61.1 28 For our between-subject study, our independent variable is Pepper trying to distract the users by mentioning different activities along with the corresponding music. Through this, we want to measure the effectiveness of music and activities in preventing people from leaving the care home, which is thereby our dependent variable. So we developed 2 different prototype designs-
29
30 Design X - It is the full interaction flow where Pepper suggests activities and uses music to distract people from leaving.
31 Design Y - It is the control condition where pepper simply tries to stop people from leaving by physically keeping its hand on the door.
32
Xin Wan 1.2 33 == Participants ==
Clara Stiller 4.1 34
Vishruty Mittal 62.1 35 17 students who play the role of having dementia. They will be divided into two groups. One group (11 participants) will be interacting with design X (group 1) robot while the other group (6 students) will interact with the design Y (group 2).
Clara Stiller 14.2 36 It is assumed that all participants are living at the same care center.
Bart Vastenhouw 1.1 37
Xin Wan 1.2 38 == Experimental design ==
Clara Stiller 4.1 39
Simran  Karnani 11.4 40 All questions collect quantitative data, using a 5 point Likert scale wherever applicable.
Clara Stiller 4.1 41
Clara Stiller 2.6 42 1. Observe the participant's mood and see how the conversation goes. Observe the level of aggression (tone, volume, pace)
Vishruty Mittal 10.1 43 1. Observe whether the mood is improved and the decision has been changed.
Simran  Karnani 1.11 44 1. Observe how natural the conversation is. (conversation makes sense)
Vishruty Mittal 10.1 45 1. Participants fill out questionnaires.
Bart Vastenhouw 1.1 46
Clara Stiller 4.1 47 == Tasks ==
Clara Stiller 2.6 48
Clara Stiller 2.7 49 Because our participants only play the role of having dementia, we will give them a level of stubbornness/ willpower with they are trying to leave. We try to detect this level with the robot.
50 Participants from group 1 (using intelligent robot) will also be given one of the reasons to leave, listed below:
Clara Stiller 4.1 51
Clara Stiller 2.7 52 1. going to the supermarket
53 1. going to the office
54 1. going for a walk
55
Clara Stiller 2.8 56 After this preparation, the participant is told to (try to) leave the building. The participant and robot have an interaction where the robot is trying to convince the participant to stay inside.
Bart Vastenhouw 1.1 57
58
Xin Wan 1.2 59 == Measures ==
Clara Stiller 4.1 60
Simran  Karnani 1.14 61 We will be measuring this physically and emotionally.
62 Physically: whether the participant was stopped from leaving the building or not.
63 Emotionally: evaluate their responses to the robot and observe their mood before and after the interaction.
Bart Vastenhouw 1.1 64
65
Xin Wan 1.2 66 == Procedure ==
Clara Stiller 4.1 67
Clara Stiller 3.1 68 {{html}}
69 <!-- Your HTML code here -->
70 <table width='100%'>
71 <tr>
72 <th width='50%'>Group 1</th>
73 <th width='50%'>Group 2</th>
74 </tr>
75 <tr>
76 <td>intelligent robot</td>
77 <td>unintelligent robot</td>
78 </tr>
79 <tr>
80 <td>
Clara Stiller 4.2 81 1. Starts with a short briefing on what we expect from the participant<br>
82 2. Let them fill out the informed consent form<br>
Clara Stiller 5.2 83 3. Tell them their level of stubbornness and reason to leave<br>
Clara Stiller 14.2 84 4. Fill out question about current mood (in their role)<br>
Clara Stiller 5.2 85 4. Let the user interact with the robot<br>
Clara Stiller 14.2 86 5. While user is interacting, we will be observing the conversation with the robot<br>
Clara Stiller 5.2 87 6. Let user fill out the questionnaire about their experience after the interaction
Clara Stiller 3.1 88 </td>
89 <td>
Clara Stiller 4.2 90 1. Starts with a short briefing on what we expect from the participant<br>
91 2. Let them fill out the informed consent form<br>
Clara Stiller 14.2 92 4. Fill out question about current mood (in their role)<br>
93 5. Let the user interact with the robot<br>
94 6. Let user fill out the questionnaire about their experience after the interaction<br>
Clara Stiller 3.1 95 </td>
96 </tr>
97 </table>
Bart Vastenhouw 1.1 98
Clara Stiller 3.1 99 {{/html}}
Clara Stiller 2.6 100
Xin Wan 1.2 101 == Material ==
Clara Stiller 4.1 102
Simran  Karnani 1.16 103 Pepper, laptop, door, and music.
Bart Vastenhouw 1.1 104
Vishruty Mittal 58.1 105 = Results =
Bart Vastenhouw 1.1 106
Sayak Mukherjee 52.3 107 {{html}}
108 <!--=== Comparison between intelligent (cond. 1) and less intelligent (cond. 2) prototype ===
Clara Stiller 6.2 109
Clara Stiller 52.1 110 {{html}}
111 <img src="/xwiki/wiki/sce2022group05/download/Test/WebHome/Stay_inside.svg" width="500" height="270" />
112 {{/html}}
113
114 Non of the participants who interacted with the less intelligent robot was prevented from leaving. Still, 3 people assigned to condition 1 weren't convinced to stay inside. A failure rate of 27,3 % is too high for this application since people could be in danger if the system fails.
115
116 **Mood evolution**
117 [[image:mood_only.png||height="150"]]
118
119 {{html}}<img src="/xwiki/wiki/sce2022group05/download/Test/WebHome/mood_before.svg" width="500" height="270" /><br>
120 <img src="/xwiki/wiki/sce2022group05/download/Test/WebHome/mood_after.svg" width="500" height="270" /><br>{{/html}}
121
122 Regarding the changes in mood, 4 out of 11 participants assigned to condition 1 had an increase in mood throughout the interaction. Only one participant felt less happy afterward, the rest stayed at the same level of happiness. The overall mood shifted to happier in general (as you can see in the graphic above), even though only small improvements in mood were detected (<= 2 steps on the scale).
123 The participants from condition 2 mostly stayed at the same mood level, 2 were less happy, one participant was happier afterward. Comparing both conditions it becomes clear, that condition 1 had a more positive impact on the participant's mood.
124
125 Interesting is also, none of the participants was in a really bad mood at the beginning or end.
126
Clara Stiller 42.1 127 ==== Condition 1 - intelligent Prototype: ====
Bart Vastenhouw 1.1 128
Clara Stiller 42.1 129 {{html}}
130 <img src="/xwiki/wiki/sce2022group05/download/Test/WebHome/Music_reco.svg" width="500" height="270" /> <br>
131 {{/html}}
Clara Stiller 40.1 132
Clara Stiller 7.2 133 8 out of 11 Participants answered, that they don't know the music that has been played. If we told them afterward the title of the song, most participants do know the song. Why didn't they recognize it during the interaction?
134 This can have two reasons: The part of the song we pick was too short to be recognized or not the most significant part of the song. For example, the beginning of "escape - the pina colada song" is not as well known as its chorus. Another reason could be, that the participant was distracted or confused by the robot and therefore couldn't carefully listen to the music.
Clara Stiller 40.1 135
136 {{html}}
Clara Stiller 40.2 137 <img src="/xwiki/wiki/sce2022group05/download/Test/WebHome/Music_fit.svg" width="500" height="270" /> <br>
Clara Stiller 40.1 138 {{/html}}
139
Clara Stiller 40.2 140 Only 4 out of 11 people agreed, that the music fits the situation. One of our claims, to use music that fits the situation or place, is therefore not reached and the music didn't have the intended effect. Even though we carefully choose the music and discussed a lot about our choice, it was hard to find music that different people connect with a certain place or activity. An approach to improve this could be using an individual playlist for each participant.
Clara Stiller 40.1 141
Clara Stiller 40.2 142
Clara Stiller 42.1 143 ==== Condition 2 - less intelligent prototype: ====
Clara Stiller 16.3 144
Sayak Mukherjee 52.3 145 Participants assigned to condition 2 weren't convinced to leave. We saw, that most of them tried to continue talking to pepper when it raises its arm to block the door, even though it didn't listen. They were surprised by peppers reaction and asked for a reason why they are not allowed to leave. In order to have a natural conversation flow, the robot should provide an explanation for each scenario that tells why the person is not allowed to leave. This confirms that our approach, to give reason to stay inside, might be helpful to convince PwD to stay inside.
Clara Stiller 42.1 146
Clara Stiller 43.1 147 === Problems that occurred during the evaluation ===
148
Clara Stiller 6.2 149 1. lots of difficulties with speech recognition:
150 1.1. even though the participant said one of the expected words, pepper understood it wrong and continued with a wrong path
151 1.2. If the participant started to talk before pepper was listening (eyes turning blue), it misses a "yes" or "no" at the beginning of the sentence, which causes misunderstandings.
152 1. problems with face detection
153 2.1. due to bad light face was not recognized
154 2.2. if the participant passes pepper from the side, the face was not recognized. Therefore, we told people to walk from the front towards pepper. In most cases that helped detect the face.
155 2.3. face detection doesn't work with face masks. This could lead to huge problems in the usage of pepper in care homes.
Clara Stiller 5.5 156
Clara Stiller 7.1 157 One of the most frequent and noticeable reactions from participants was **confusion**. This feeling was caused by two main factors:
158 misunderstandings from speech recognition which leads to unsuitable answers from pepper, as well as the unsuitable environment and setting of our evaluation.
Clara Stiller 6.2 159 The reasons for failure in speech recognition are listed above. An unsuitable answer can e.g. be an argument to stay inside, that doesn't fit the participant's reason to leave. Also, some people told in a long sentence that they don't like the provided activity and still want to leave. If the speech recognition fails in this case and pepper understood you would like to do the activity, it seems like it encourages you to leave, instead of doing the activity. This leads to the total opposite of our intention.
Sayak Mukherjee 52.3 160 Furthermore, we found out, that our prototype doesn't fit in the environment of the lab. We encourage the participant to do some activities, that they can't do in the lab environment (go to the living room, have a coffee or do a puzzle). If the robot tells asks you if you want to do the activity, most people don't know how to react and are insecure about how to answer. Participants "freeze" in front of the robot or just left the room. -->
161 {{/html}}
Clara Stiller 6.2 162
Sayak Mukherjee 52.3 163 === RQ1: Are people convinced not to go out unsupervised? ===
Vishruty Mittal 58.1 164
Sayak Mukherjee 52.3 165 {{html}}
166 <table style="width: 100%">
167 <tr>
168 <td style="width: 50%">
Sayak Mukherjee 54.1 169 <img src="/xwiki/wiki/sce2022group05/download/Foundation/Operational%20Demands/Personas/WebHome/RQ1.jpg?height=250&rev=1.1" />
Sayak Mukherjee 52.3 170 </td>
171 <td>
172 Comment on the graph
173 </td>
174 </tr>
175 </table>
176 {{/html}}
Clara Stiller 42.1 177
Sayak Mukherjee 52.3 178 === RQ2: How does the interaction change the participant's mood? ===
Vishruty Mittal 58.1 179
Sayak Mukherjee 52.3 180 {{html}}
181 <table style="width: 100%">
182 <tr>
183 <td style="width: 50%">
Sayak Mukherjee 54.1 184 <img src="/xwiki/wiki/sce2022group05/download/Foundation/Operational%20Demands/Personas/WebHome/RQ2.jpg?height=250&rev=1.1" />
Sayak Mukherjee 52.3 185 </td>
186 <td>
187 Comment on the graph
188 </td>
189 </tr>
190 </table>
191 {{/html}}
Bart Vastenhouw 1.1 192
Sayak Mukherjee 52.3 193 === RQ3: Can the robot respond appropriately to the participant's intention? ===
Vishruty Mittal 58.1 194
Sayak Mukherjee 52.3 195 {{html}}
196 <table style="width: 100%">
197 <tr>
198 <td style="width: 50%">
Sayak Mukherjee 54.1 199 <img src="/xwiki/wiki/sce2022group05/download/Foundation/Operational%20Demands/Personas/WebHome/RQ3.jpg?height=250&rev=1.1" />
Sayak Mukherjee 52.3 200 </td>
201 <td>
202 Comment on the graph
203 </td>
204 </tr>
205 </table>
206 {{/html}}
Bart Vastenhouw 1.1 207
Sayak Mukherjee 52.3 208 === RQ4: How do the participants react to the music? ===
Vishruty Mittal 58.1 209
Sayak Mukherjee 52.3 210 {{html}}
211 <table style="width: 100%">
212 <tr>
213 <td style="width: 50%">
Sayak Mukherjee 54.1 214 <img src="/xwiki/wiki/sce2022group05/download/Foundation/Operational%20Demands/Personas/WebHome/RQ4.jpg?height=250&rev=1.1" />
Sayak Mukherjee 52.3 215 </td>
216 <td>
217 Comment on the graph
218 </td>
219 </tr>
220 </table>
221 {{/html}}
Bart Vastenhouw 1.1 222
Sayak Mukherjee 52.3 223 === RQ5: Does the activity that the robot suggests prevent people from wandering/ leaving? ===
Vishruty Mittal 58.1 224
Sayak Mukherjee 52.3 225 {{html}}
226 <table style="width: 100%">
227 <tr>
228 <td style="width: 50%">
Sayak Mukherjee 54.1 229 <img src="/xwiki/wiki/sce2022group05/download/Foundation/Operational%20Demands/Personas/WebHome/RQ5.jpg?height=250&rev=1.1" />
Sayak Mukherjee 52.3 230 </td>
231 <td>
232 Comment on the graph
233 </td>
234 </tr>
235 </table>
236 {{/html}}
Clara Stiller 16.3 237
Sayak Mukherjee 52.3 238 === RQ6: Can pepper identify and catch the attention of the PwD? ===
Vishruty Mittal 58.1 239
Sayak Mukherjee 52.3 240 {{html}}
241 <table style="width: 100%">
242 <tr>
243 <td style="width: 50%">
Sayak Mukherjee 54.1 244 <img src="/xwiki/wiki/sce2022group05/download/Foundation/Operational%20Demands/Personas/WebHome/RQ6.jpg?height=250&rev=1.1" />
Sayak Mukherjee 52.3 245 </td>
246 <td>
247 Comment on the graph
248 </td>
249 </tr>
250 </table>
251 {{/html}}
Clara Stiller 16.3 252
Sayak Mukherjee 52.3 253 === Reliabity Scores ===
Vishruty Mittal 58.1 254
Sayak Mukherjee 52.3 255 {{html}}
256 <table style="width: 100%">
257 <tr>
258 <td style="width: 50%">
Sayak Mukherjee 54.1 259 <img src="/xwiki/wiki/sce2022group05/download/Foundation/Operational%20Demands/Personas/WebHome/RelScores.jpg?height=250&rev=1.1" />
Sayak Mukherjee 52.3 260 </td>
261 <td>
262 Comment on the graph
263 </td>
264 </tr>
265 </table>
266 {{/html}}
267
Vishruty Mittal 58.1 268 = Limitation =
Clara Stiller 16.3 269
Sayak Mukherjee 52.3 270 * **Lab Environment**: The lab environment is different from a care home, the participants found it difficult to process the suggestions made by Pepper. For example, if Pepper asked someone to visit the living room, it created confusion among the participants regarding their next action.
Clara Stiller 52.2 271
Sayak Mukherjee 52.3 272 * **Role-Playing**: Participants for the experiment are not actual patients suffering from dementia. Hence it is naturally difficult for them to enact the situations and replicate the mental state of an actual person suffering from dementia.
Clara Stiller 52.2 273
Sayak Mukherjee 52.3 274 * **Speech Recognition**: The speech recognition module inside Pepper is not perfect. Therefore, in certain cases, Pepper misinterpreted words spoken by the participants and triggered an erroneous dialogue flow. The problems commonly occurred with words that sound similar such as "work" and "walk". Moreover, there are some additional hardware limitations that hampered the efficiency of the speech recognition system. One prominent issue is that the microphone within Pepper is only active when the speaker is turned off. A blue light in the eye of Pepper indicated the operation of the microphone. Since most of the participants are not used to interacting with Pepper found it difficult to keep this limitation in mind while trying to have a natural conversation.
275
276 * **Face Detection**: The face recognition module within Pepper is also rudimentary in nature. It can not detect half faces are when participants approach from the side. Adding to the problem, the lighting condition in the lab was not sufficient for the reliable functioning of the face recognition module. Hence Pepper failed to notice the participant in some cases and did not start the dialogue flow.
277
Xin Wan 1.2 278 = Conclusions =
Vishruty Mittal 58.1 279
Sayak Mukherjee 52.3 280 * People who liked the activity tend to stay in
281 * People who knew the music found it more fitting
282 * People are more convinced to stay in with the intelligent prototype
283 * Cannot conclude whether moods were improved
284 * Need to experiment with the actual target user group to derive on concrete conclusion
285 * Experiment with personalization
Clara Stiller 40.1 286
Sayak Mukherjee 52.3 287 = Future Work =
Vishruty Mittal 58.1 288
Sayak Mukherjee 52.3 289 * **Personalisation**: Personalize music, and activity preferences according to the person interacting with Pepper.
290 * **Robot Collaboration**: Collaborate with other robots such as Miro to assist a person with dementia while going for a walk instead of the caretaker.
291 * **Recognise Person**: For a personalised experience, it is essential that Pepper is able to identify each person based on an internal database.
292 * **Fine Tune Speech Recognition**: Improvements are necessary for the speech recognition module before the actual deployment of the project in a care home. Additionally, support for multiple languages can be considered to engage with non-English speaking people.