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| Author | Paper | IoT technology used | Conclusion |
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| Ishii et al. [30] | An Early Detection System for Dementia using the M2M/IoT Platform | M2M IoT based sensors, clouds, and actuators were used to observe the behaviour of the person, and then the collected data were compared with the available listed expected behaviour of the patient. | The complete system was capable of detecting the disease in people who are living alone and having no one to observe their behaviour. |
| Rovini et al. [31] | How Wearable Sensors Can Support
Parkinson’s Disease Diagnosis and Treatment: A Systematic Review | Wearable sensors were used for the early diagnosis of the dementia, to observe any kind of shaking and to detect extraordinary movements and fluctuations in the body. | The idea behind system generation was to develop an IoT-based perfect system that must be capable of diagnosing dementia and monitoring the patient’s behaviour at an early stage so that the situation can be controlled before getting worsen. |
| Hernandez-Penaloza et al. [32] | A Multi-Sensor Fusion Scheme to Increase Life
Autonomy of Elderly People with Cognitive Problems | The system was composed of multiple sensors positioned at the patient’s home to observe the activities and to take an action in case any abnormality is found. It used a multimodel approach to increase the accuracy of the sensors. The installed sensors wearable bracelets. Wireless sensor network was used to monitor the patient if they left home. | Clinical diagnosis was able to detect the disease progress by observing the activities when the patient was home, which helped better diagnose and detect the problem at the beginning. |
| Garcia-Magarino et al. [33] | Framework-Supported Mechanism of Testing Algorithms for Assessing Memory and Detecting Disorientation from IoT Sensors | The researchers created a 3D real-time environment and fixed IoT-based sensors into that environment and applied two algorithms: one was capable of detecting memory of the patient and another one was applied to observe any change in the routine activities or behaviours of the patient with the help of sensors. The algorithms were capable of identifying changed behavioural pattern and thus diagnose the problem at an early stage. | If implemented by practitioners, the used algorithm was capable of identifying memory loss and dementia if it actually occurs. |
| Chong et al. [34] | Predicting Potential Alzheimer Medical Condition in Elderly using IOT Sensors: A Case Study | The researchers tried to use sensors like RFID-enabled hand band along with IR room locator to observe the activities of elderly people in their homes. Three variables were used that are capable to identify whether the person has dementia or not. Furthermore, using these three variables, a prediction model was generated to predict the disease by obtaining the sensor data. The sensors can sense the patient’s condition by observing patient’s activeness or negligence through monitoring gas, water taps, electric switches, and TV being switched on and off. | Although the system worked well in identifying the mental state of the person, there were some drawbacks. First was the quality of the used sensors. Good quality sensors were able to provide more accurate results. Second was the model providing the same results for Parkinson’s disease, Alzheimer’s disease, and dementia. |
| Tan and Tan [35] | Early Detection of Mild Cognitive Impairment in Elderly through IoT: Preliminary Findings | The researcher proposed a methodology to identify the symptoms of elderly people that leads to the beginning of dementia and immediately starting proper medication to slow down the illness as there is no proper medicine that can completely stop the dementia. Tractable and unnoticeable IoT-based sensors were implanted in the houses of two sets of people: one set for healthy people and another set for people that are suffering from behavioural changes. Collected data of sensors from both sets were compared, and then, a pattern was analysed to identify whether the person is healthy or not. | Early results were obtained because using IoT devices was a fruitful step in starting the treatment. |
| Enshaeifar et al. [36] | Internet of Things for Dementia Care | Here, the researchers proposed a method named technology integrated health management. TIHM was applied with the help of IoT devices. Various machine learning algorithms had been used to foster the information of the patient. TIHM has the capability to work in real-time environment and to notify healthcare professional of the continuous health status of the person suffering from dementia. | The system is able to work in real-time environment to retrieve the required information and provide more and suitable information to the patients and the doctors, but the system has reliability and trust issues. |
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