2.1. Health Focus
The health focus aspect represents the healthcare-related, medical, or clinical aims the studies examine. Some of them are ailments and disease types or general “healthcare” and “eldercare”. In the former category, we find “dementia” in all its forms and pre-stages, including subjective cognitive impairment (SCI) and mild cognitive impairment (MCI) [27
], and “Alzheimer’s” (AD) as a special case of sever dementia, “Parkinson’s” disease (PD), “CVD”, “frailty and falls”, “orthopedics”, “robotic surgery”, “pulmonary” disease, “anxiety”, “obesity”, “sleep disorders”, or “chronic disease” in general. To begin with, eldercare refers to care of elders with no specific ailment in mind, but rather monitoring and maintaining an active and healthy lifestyle in old age, prolonging independent living (so-called living in place), also referred to as active and healthy ageing (AHA) and often achieved through ambient, smart home, unobtrusive assistive technology-the so-called ambient assisted living (AAL) [23
]. Beyond general healthcare and into specific ailments, AD and dementia are the most prominent of them. Although AD is a subtype, or a severe, progressed stage of dementia, some studies focus especially on that, such as Surendran et al. [15
]. Others refer to the general spectra of dementia and AD alike, such as [8
]. Dementia is sometimes presented as a sole health focus [14
] or examined along other chronic disease in general [4
] or frailty and falls [16
]. PD is a popular health focus [9
] combined with AD and dementia, and even CVD [11
]. The study in [26
] considers general eldercare, that is, prolonged independent living, as well as falls related to frailty.
In the less popular application areas, a lot of wearable devices can detect parameters such as blood pressure [20
] and oxygen levels in blood [17
], and thus constitute a very useful tool in the hands of persons with diabetes in CVD [19
], arthritis, and orthopedics [13
]. These devices measure sleep and asthma, related to anxiety and sleep disorders [18
], as well as general eldercare [22
]. Some reviews consider general healthcare provision, which includes eldercare [6
], and focus on the more technical aspects such as encryption and data safety [28
], examined in the next sections.
2.2. IoT Technology
The IoT technology aspect considers the various IoT wearable sensors and devices found in earlier review studies, mainly categorized in “wearables”, “smartphones”, “robotics”, “smart home”, “environmental sensors”, “indoor positioning”, “biometric sensors”, (fixed) “cameras”, “wearable cameras”, “microphone”, and “applications”. While all categories refer to specific hardware, the latter refers to any type of software and AI algorithm on local PCs or the cloud, which does not require a hardware IoT component of the former categories.
The study in [26
] considers five types of devices: PIR motion sensors, body-worn sensors, pressure sensors, video monitoring, and sound recognition. Our review generalizes further to include more device types that are not considered there; for example, PIR motion sensors and pressure sensors are included in “smart home” sensors along with other possible types such as door-widow sensors, appliance and object usage sensors, and so on. Body-worn sensors are essentially “wearables”, and video monitoring and sound recognition are mapped to “cameras” and “microphones”, respectively, in our review.
To begin with, “wearables” are dominant in the literature, owing to their increasing popularity and affordability. Cedillo et al. [22
] selected the most relevant devices to an AAL context, combining “wearables” and “applications” that contribute to the wellbeing of elders. Piwek et al. [18
] includes various types of wearables, such as headbands, sociometric badges, camera clips, smartwatches, and sensors embedded in clothing, while Haghi et al. [6
] deal with nine different motion trackers and four commercially available wrist-worn devices in the market for vital signs measurement, that is, FitBit, Jawbone, Withings, and Misfit. Another study [24
] complements this list of commercial wrist-worn devices with Apple iWatch, Samsung Gear S2, Pebble Time, UP4 by Jawbone, Empatica, and Fitbit Flex, among others, through head-mounted devices and other accessories, such as smart jewelry, e-textiles, skin patches, and even an e-tattoo. In addition to both commercial devices and research prototypes, this review also examines pertaining potential security threats and confidentiality issues. Surendran et al. [15
] explores smart wearable locator band, smart socks, the CleverCare Smart watch, iTraq, MedicAlert Safely Home, PocketFinder, Trax, and wearable cameras.
Biometric sensors are a special type of wearable or non-wearable devices that are used for both continuous and on-demand measurement of physiological and medical data. While they are often applied to security, for example, through fingerprint scanning, they are also used in healthcare, for example, measuring body temperature, electrocardiogram (ECG), pulse oxygen saturation, blood pressure, blood glucose, and so on [29
]. Patel et al. [11
] examines both smart home sensors for in-house positioning and microphones to record audio and voice, as well as a wide range of biometric sensors for glucose, pH, and O2 measurements. Another study [9
] deals with what IoT offers to the neurological aspects of health disorders, examining devices that can be classified as both “wearables” and ”biometric sensors”, such as the Basis Health Tracker, Misfit Shine, Fitbit Flex, Withings Pulse O2, Actiwatch Spectrum, FitBit, Empatica 4, Bittium Faros, and PhysioCam. It also mentions an in-ear sensor for EEG (electroencephalogram). The study in [19
] examines four wearables from a medical point of view, namely, Myo, Zyo patch, MyDario, and SleepBot. Along those lines, the study of [20
] examines wearables and biometric sensors for diabetes, heart monitoring, and pulmonary disease, including radio-frequency identification (RFID) and wireless sensor networks (WSN) parameters.
Smart home devices are usually ambient and inobtrusive in an AAL context. A study from Wang [17
] reviews indoor positioning systems, emphasizing on human activity recognition, as well as biometric sensors (vital sign monitoring, blood pressure, and glucose). Blackman et al. [25
] consider three generations of AAL, gathering 64 studies, and consider parameters such as social support, interface, and health monitoring capabilities. They include wearables and smart home sensors (AiperCare, Aladdin, bed occupancy sensor, and so on), as well as environmental sensors such as gas detectors. The review in [14
] deals with most types of “smart home” ambient sensors, “wearables” and “wearable cameras”, e-textiles, and “indoor positioning” systems, especially oriented around AAL projects.
Fall detection, prevention, and risk assessment mainly involve wrist-worn sensors, RFID sensors, and a footwear, as reviewed in Baig et al. [23
]. The researchers in [16
] also review AAL platforms, with wearables and smart home sensors to enable multimodal fall detection. Related to that, Ienca et al. [8
] cover a wide area of intelligent assistive technologies around mobility and rehabilitation aid.
2.3. Review Criteria
Review criteria are used in earlier studies to evaluate, examine, and classify solutions offered in the surveyed case studies. In this paper, they are classified as follows: “sensor types”, “data format”, “ease of use”, “efficacy”, “invasiveness”, esthetics”, “performance”, “networking”, “ontologies”, “safety”, “security”, “robustness”, “cost”, “energy consumption”, “accuracy”, “range”, “social inclusion”, and “clinical value”.
The first set of criteria considers IoT technology and infrastructure parameters such as sensor types, networking architecture, and communication protocols. Salih et al. [13
] refer to sensor types in wireless sensor networks (WSNs) for various sensing modalities, while also reviewing algorithms and intelligence applications of artificial neural networks (ANNs), activity prediction, and decision making. Similarly, the study in [10
] reviews sensor characteristics, existing AAL platforms that stem from collaborative projects, and activity recognition systems.
Sensor types and networking are also considered in Banaee et al. [12
], who additionally examine data mining from wearables to provide valuable information. Li et al. [4
] review smart home and health care solutions, while emphasizing healthcare, rehabilitation, and AAL infrastructure with mobility assistance applications of robotic service platforms, multi-agent systems, and other human machine interfaces. Lee et al. [21
] explores the field of sustainable wearables, while Surendran et al. [15
] explores the networking and accuracy of several wearables and cameras. The study in [26
] considers the types of sensors in five categories and especially their efficacy in various short studies (non-longitudinal).
Networking also entails communications and, many times, the data acquisition techniques. The study in [10
] considers the various types of communication between devices and gateways, usually smartphones or PCs. Transmitter and receiver size is mentioned in [11
], where a smaller size may be beneficial to weight, but reduces performance in transmission bandwidth. Banaee et al. [12
] consider data acquisition for training algorithms as a criterion. Moreover, Li et al. [4
] examine communications between devices as well as software agents in multi-agent systems. Some other technological aspects taken into consideration in some reviews are data format and data rate [14
]; networks, data sets, models, and ANNs [12
], update rate, data output, and algorithms [17
]; or CPU, connectivity, memory, GPS, RAM, display, design, and communication capabilities [24
When considering infrastructure, performance, and sustainability, energy consumption is also considered [11
]. This plays an important role in portables and wearables as it attributes to comfort, but increases size [20
]. Referring to elders, long battery life-and thus low power consumption-is all the more critical [23
], as they are not familiar with consistently charging their devices. Thus, battery issues need to be minimal, or ideally, not exist at all [24
]. Battery size and comfort usually relate to cost, but wearables become increasingly more portable, long-lasting, and affordable in retail, but maybe less durable and accurate [10
Regarding security, Azzawi et al. [28
] review data acquisition, processing, and analyzing parameters of body wearable sensors. They identify the need for secure infrastructure, in terms of new authentication mechanisms tailored to IoT devices. Network architecture [4
] and strong authentication and encryption [28
] can be different aspects of each device. Data security, in general, is a very important parameter [13
]-the study of [18
] and other reviews categorize devices with this criterion quite often.
Important criteria when it comes to healthcare and the elderly revolve around ease of use, size, and invasiveness, which ultimately shape the acceptance factors of the technology. This criterion is a fundamental concern for several studies [9
]. The latter study also considers “easy installation”, which is an important parameter as well. More aspects relate to ease of use, such as compactness in [11
], connectivity and easy device management [19
], weight [6
], and whether the user needs to operate a device or not [17
]. Piwek et al. [18
] also include the criterion of “behavioral effect”, which examines whether a device alters the user’s behavior in their everyday life. Blackman et al. [25
] review the importance of a specialized user interface, as every user has different technological competence and literacy. Moreover, an emergency button is examined as a useful functionality of wearables for elders. Finally, esthetics also play a role in elderly users, many times with respect to stigma [9
Some studies go into clinical validation, such as Ienca et al. [8
], which takes into consideration the evidence of clinical validation for each device and the direct applicability to their health focus. Moreover, in [9
], the wearables’ efficacy in the current health focus was reviewed. Lastly, two important criteria are safety [21
] and daily tasks evaluation-two aspects of elders’ everyday life, which is the primary focus.