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| Type of technology | Objectives | Examples of applications | Some limitations |
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| Sensors (36 studies) | | | |
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| Inertial sensors (accelerometer, gyroscope, magnetometer) (17 studies) [20, 21, 23, 48, 53–65] | Recognizing physical activity and status of patients (standing, sitting, lying down, walking) [55, 61, 65] | (i) Using wearable sensors attached to the chest and shoes [54] or using them as a tag [20, 55], bracelet,
and belt [59, 62]
(ii) Diagnosing and predicting
falls [20, 60, 62]
(iii) Extracting movement patterns [62] | Current accelerometers do not specify place of performing activities at home [64] |
|
| Switch sensors (14 studies) [23, 26, 29, 47, 49, 55–57, 59, 62, 63, 66–68] | Installing switch sensors on doors and home appliances to monitor their use [49, 57, 66] | (i) Recognizing proper performance of activities and activity duration
[23, 63, 68]
(ii) Monitoring the entering and leaving to/from the living places [63, 68] | (i) Relatively high energy consumption when sending and displaying information on the monitors [68]
(ii) Producing incorrect and repetitive information due to the entry and exit of people other than patients [49] |
|
| Sensors for vital signs (11 studies) [21, 23, 24, 26, 47, 58, 59, 63, 68–70] | Getting information about the patient’s health including physical activities and vital signs [21, 23] | (i) Receiving data on blood pressure, body temperature, pulse, oxygen saturation, weight and hydration, daily step count and amount of physical activity, respiratory rate, and body movement, even during sleep [24]
(ii) Using sensors in different ways including monitors installed at homes [24], wearable sensors [47, 63], sensors in belt [69], and sensors in mat [58]
(iii) Recording data in sleep or awake modes [69, 70] | Possible impairment in estimating heart rate and breathing rhythm during sleep due to type of body movement in sleep [69, 70] |
|
| Pressure sensor (17 studies) [21, 23, 24, 26–28, 48, 50, 57–59, 63, 64, 67, 68, 71, 72] | Using sensors to measure body movement and monitoring sleep pattern [28, 58] | (i) Measuring bedtime, sleep duration and breaks, and sleep quality [21, 50, 67]
(ii) Recognizing the person’s agitation and wandering duration [68]
(iii) Activating the alarm after the person getting out of bed [63, 72] | Misrecognizing the sleep mode when the person is calm and motionless in bed [71] |
|
| Infrared (IR) sensor (15 studies) [20, 22, 23, 26, 28, 50, 53, 55, 58, 62, 63, 66, 68, 71, 73] | Monitoring the places where the person is present during the day and night using activity recognition [63] | (i) Activity recognition
[23, 55, 68, 73]
(ii) Examining sleep patterns [50] | (i) Difficulty in recognizing the person’s location when other people are present [55]
(ii) Failure to record information when the person is motionless (e.g., watching TV in the bed) [58] |
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| Cameras (18 studies) | | | |
|
| Red-green-blue-depth (RGB-d) camera (16 studies) [21–23, 29, 47, 53, 54, 57, 59, 60, 62, 67, 70, 72, 74, 75] | Depth cameras collect images and depth data and provide various data such as RGB, depth, infrared, patient skeleton movement recognition, and tracking data. Analyzing these data makes it possible to monitor patients’ progress during rehabilitation
exercises [29, 60, 70] | (i) Tracking the patients using a camera along with inertial sensors or IR [23]
(ii) Depth cameras are better in predicting patient status than wearable sensors [21, 74]
(iii) Identifying the person’s movement direction using a variety of cameras and sensors [72] | Lack of enough accuracy for differentiating the activities related to the joints and small actions (e.g., eating and taking medication both involve the hand joints) [60] |
|
| Ordinary (cameras without sensors) (5 studies) [47, 59, 69, 71, 74] | Video camera is used at smart homes in different places [59]. This camera provides a panoramic view of the scene (360 degrees), which allows monitoring large indoor areas such as day-care
centers [47, 59] | (i) Establishing a video surveillance system to prevent unwanted accidents for the patient during daily high-level activities such as cooking [47, 59]
(ii) Improving the results of human tracking algorithms due to producing more comprehensive data by these types of devices [59] | A large volume of data is gathered by this type of camera, and a great amount of additional data is gathered by the recorded images [59] |
|
| Global positioning system (GPS) (7 studies) [23, 24, 27, 48, 50, 60, 61] | Tracking or positioning systems can indicate the location of the person with dementia [48, 61] | (i) Providing security for patients with dementia, especially when they suffer from agitation and depression [48]
(ii) Easy access due to being used in various devices such as
mobile phones [24]
(iii) Ability to send location to caregivers via short message service (SMS) [24]
(iv) Easy to use due to the small size of the devices [24, 61] | (i) GPS is not accurate enough indoors to locate the person [23]
(ii) Using GPS for tracking is not suitable due to the error of about 8 m when a serious danger threatens a person in a path as they approach a certain point [23]
(iii) High energy consumption of these devices and the need to charge the batteries daily (this limitation can be serious for people with dementia) [24, 50]
(iv) If it is difficult for a person to use, fasten, and carry a GPS safety bracelet, they are reluctant to use it and, sometimes, remove it. Locked models are suggested in this case [48] |
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| Communication technology | | | |
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Bluetooth (4 studies)
[22, 50, 63, 68] | (i) Using Bluetooth technology to detect objects by tags that are enabled by proximity beacon [22, 68]
(ii) Using this technology to transfer the gathered data to the main
server [22, 50, 68] | (i) Possibility of installing positioning sensors on the walls along with Bluetooth tags attached to wheelchairs and patient equipment for tracking patients, especially when people with cognitive impairment disconnect wearable devices or those attached to the body [50] | |
|
ZigBee (3 studies)
[27, 55, 61] | (i) Using ZigBee to identify the person’s location [27]
(ii) Using this technology to make communication between the sensors around the person and central server [27] | (i) Appropriate accuracy using ZigBee along with IR sensors and combining the data of these two to locate the person [55] | (i) ZigBee is commonly used in conjunction with other technologies and most of the people are reluctant to carry multiple devices, so ZigBee application is limited [61]
(ii) High energy consumption in ZigBee-equipped devices and the importance of improving battery life as a simple way to increase system reliability [55, 61] |
|
Radio frequency identification (RFID)
(1 study) [50] | Each active entity should be equipped with barcode-sized tags for unique identification. The data transmitter to the RFID server periodically retrieves the data from the tags and transmits them via Wi-Fi or Bluetooth [50] | (i) Increasing use of RFID in Internet of Things (IoT) to connect entities to the Internet [50] | |
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| Near field communication (NFC) (1 study) [60] | Measuring devices containing NFC equipment are installed in fixed locations to determine the position and recognize activities [60]. | (i) Installing an NFC tag on a specific place such as a dining table to sense the NFC tag installed on the medicine box and diagnose medicine consumption by the patient [60] | NFC should be used along with a camera to improve accuracy in recognizing activities [60] |
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