## 7 Conclusions  
In this paper, we proposed an edge computing-based self-organized device network and developed three types of smart devices (wearable, tag, and stationary) to collect a user's ADL in his or her living space. We adopted the edge computing method to categorize and analyze the activities that a user performs in each indoor unit space. The wearable device can be easily equipped by the user, and the tag and stationary devices can be installed by attaching sensors to home appliances or doors; consequently, these devices are also applicable to a typical existing house. The ADL measurement system can collect a user's daily activities and determine who acted, where the activities were performed, and whether the activities were finished successfully or abnormally. It is also possible to record the physical ability of the user to move between indoor fixed spaces. Data on the daily activities, forgetfulness history, and walking speed of a user can be recorded in his or her wearable device; these data can be used by a doctor or guardian to diagnose the mental and physical health of a patient more accurately compared to interviews with the patient in a hospital. We described a service scenario in daily home life using the proposed self-organized device network and evaluated the power consumption of the tag device and the preparation time based on the user's position. We also measured several activities that could be measured in a home environment using the tag device, and we calculated the accuracy of the measurements. The proposed system determines whether a user's behavior was successful or abnormal using installed smart devices to collect the user's activities at home. Our approach is different from directly measuring the brain signals of patients with mental disorders using Brain-Computer Interface (BCI) devices. A patient with a brain injury may be able to perform basic activities well in daily life. It is also possible to identify changes in THE ADL performance of these patients using the proposed system. However, in the future, we plan to test our system with real patients who have a mental illness. The examination of patients' ADL ability based on the severity of their mental disorder can confirm the medical validity of the proposed system. Furthermore, we seek to recognize specific individuals by adopting a user-recognition method that uses foot pressure characteristics measured while a user steps on a footpad [38]. Moreover, we plan to improve the accuracy of appliance-usage measurements using a tag device and add a wide variety of home items to the system. Finally, we expect to obtain the long-term history of activities, forgetfulness, and moving ability of the patients and analyze the physical and mental health of patients using a machine-learning algorithm. [PERSON] designed and performed experiments, evaluated the data, and wrote the paper; [PERSON] partially designed and performed experiments; [PERSON] supervised the research project related to this paper and edited the manuscript. All authors have read and agreed to the published version of the manuscript. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{1}{c}{\multirow{2}{*}{**Activity**}} & \multicolumn{2}{c}{**Execution**} & \multicolumn{1}{c}{**Success**} & \multicolumn{1}{c}{**Accuracy**} \\  & \multicolumn{2}{c}{**(Number of Times)**} & \multicolumn{1}{c}{**(Number of Times)**} & \multicolumn{1}{c}{**(\%)**} \\ \hline \multirow{2}{*}{Door Entrance} & Enter & 200 & 195 & 97.5 \\  & Exit & 200 & 196 & 98 \\ \hline \multirow{2}{*}{Faucet} & Turn on & 150 & 145 & 96.7 \\  & Turn off & 150 & 132 & 88 \\ \hline \multirow{2}{*}{Gas Stove} & Turn on & 150 & 146 & 97.3 \\  & Turn off & 150 & 140 & 93.3 \\ \hline \multirow{2}{*}{Refrigerator} & Open & 150 & 145 & 96.7 \\  & Close & 150 & 143 & 95.3 \\ \hline \multirow{2}{*}{Microwave} & Open & 150 & 145 & 96.7 \\  & Close & 150 & 143 & 95.3 \\ \hline \multirow{2}{*}{Rice Cooker} & Open & 150 & 148 & 98.7 \\  & Close & 150 & 148 & 98.7 \\ \hline \hline \end{tabular}
\end{table}