Wearable technology refers to a large class of electronic and mobile devices that are integrated into implants, accessories, or outfits and can be worn on the body as portable measurement tools (Gao et al. 2015). This technology also includes the software applications with analytic algorithms embedded in wearable devices (Schüll 2016). These technologies can connect to communication infrastructure; sense, store, and transmit data; and perform some computations (Hiremath et al. 2014; Godfrey et al. 2018). Due to their small size and ease of usage, these wearable technologies have increasingly been applied to provide smarter solutions in healthcare-related fields.
Aging population is a current challenge for most healthcare systems around the world besides other issues such as high healthcare operational cost (Wamba and Ngai 2011; Reyes et al. 2012) and quality concerns (Reyes et al. 2012). The number of older adults only in the USA is anticipated to double by 2030 (Chen et al. 2010). These people require more care and attention (Singh and Kaur 2010), and they have an increased prevalence of chronic illnesses which are expensive to treat (Powell 2009) and inevitably result in demanding more health resources and expenses. Most older adults prefer to continue their independent lifestyle while it is vital to maintain their health status. Some of them suffer from chronic illnesses and require to have constant health monitoring. To this end, remote healthcare monitoring could benefit them and increase their quality of life (Dierckx et al. 2015) and reduce hospitalization. By keeping senior citizens out of hospital, the amount of pressure on the healthcare system is expected to reduce, and as a result, the healthcare expenditure may decrease.
One of the technologies that can be used for remote healthcare monitoring is wearable technology. Wearable technology can monitor vital signs or human movement. It thus offers a huge potential for transforming healthcare. In the following sections, an overview on healthcare challenges with regard to aged population and then a review of wearable technology applications to address healthcare requirements of older adults are discussed. Finally, the entry is concluded with future research directions and the summary of wearable technology and their applications for older adults in the healthcare industry.
Wearable Technology Components and Their Role in Healthcare
Wearable technology is a part of Internet of Things (IoT) which is a technological phenomenon that stems from new advances and ideas in ICT. IoT and consequently wearable technologies can be related to communication/connectivity, ubiquitous, pervasive computing, and ambient intelligence (Dohr et al. 2010). Based on the wearable device types, they can be classified into the following categories: (i) embedded wearable devices or implants, (ii) mounted devices attached (non-covert) on the body, and (iii) carried devices carried out close to the body (Kirby and Mosley 2015).
Sensor layer: it is the interface between the device and the human body that captures data and monitors the measurement signals.
Processing layer: it collects sensor’s signals to provide a high-level outcome for the application layer.
Application layer: it provides feedback or a representation of the monitored signals to the wearers or the other involved users (e.g., healthcare team).
Wearable technologies embrace different electronic-based sensors and sensing devices depending on their specific applications and measurement needs (Scilingo et al. 2011; Godfrey et al. 2018). A number of technologies that are being used in wearable devices are IoT sensors, RFID, GPS, and infrared sensor. Through these technologies, different types of data such as movement, body temperature, and location can be collected.
Regardless of the device and sensor types, wearable devices have the ability to capture and transmit real-time data in the form of electronic signals in a periodic or continuous form, for a particular patient/object in a specific location. A wearable device enables human-objects, human-human, and objects-objects connections, communication, information sharing, and decision coordination. Accordingly, a range of functions are included in wearable technologies, such as data collection from on/in body sensors, data pre-processing, storage, and transfer (Hiremath et al. 2014). The data transfer could be either to immediate neighbors (e.g., mobile phone) or to a remote server.
As the wearable technologies become robust (Kirby and Mosley 2015), have the abovementioned features, and are increasingly miniaturized, their applications in healthcare have attracted significant attention of researchers. These technologies have the potential to revolutionize the way healthcare services are delivered and the way people demand these services. They can provide the aiding tools to support patient assessment, treatment, and management activities (Godfrey et al. 2018) and to provide automation for remote healthcare interventions such as diagnostic monitoring and treatment (Hiremath et al. 2014). Wearable technologies can also enable healthcare systems to overcome some of their challenges and to be more accessible to the broader range of the population in a more efficient and effective manner.
Considering the potential features of wearable technologies, they can provide many solutions to address the challenge of population aging and chronic disease management. For example, as the wearable technologies can provide remote monitoring features, they can provide technology solutions that help people to maintain their independent lifestyle while continuously monitoring their healthcare status. As a result, they could potentially reduce the cost of healthcare services. Also, as mentioned by Cacho-Elizondo et al. (2017), wearable technologies could enhance the diversity in treatments and therapies, increase certainty in diagnoses, decrease the rate of error, and improve patient’s safety due to 24-h 7-day information availability both in the normal care or emergency situations.
Key Research Findings
According to the parameters to be monitored, wearable technology applications for geriatric care can be classified into two categories. One category is for capturing kinematic parameters of the body segments, and the other category is for monitoring physiological signs (Scilingo et al. 2011). In the former group, body movement and gesture are monitored to detect any disturbances in the movement. While in the latter category, physiological signs such as respiratory or heart bit rate are being monitored.
Based on the purpose of applications, wearable technologies can be classified into chronic care monitoring, aged care monitoring and support applications, emergency applications, and rehabilitations. The following sections present a review of these groups.
Wearable Technologies for Chronic Disease Monitoring
Tele-monitoring for older adults and ensuring their medication compliance (Dohr et al. 2010) is one of the most promising applications of wearable devices and IoT in healthcare. This application addresses the requirements of those older people who value independent living, while their health condition needs to be continuously monitored and assessed by the healthcare providers.
Chronic disease monitoring is an efficient way of managing chronic diseases in older adults (Kalid et al. 2017). Due to the high rate of chronic disease in this population, considerable expenses of healthcare are allotted to this group. Continuous monitoring of vital signs of these patients helps to decrease the number of rehospitalizations (Fanucci et al. 2013) and to provide convenience for older people; therefore, a significant number of wearable technology studies are focused on developing in-home monitoring systems. This group of applications can enable physicians in monitoring the vital signs, or early detection of any anomalies that, in turn, could result in appropriate and timely medical interventions (Fanucci et al. 2013), thus can present timely care to patients without affecting their comfort and preference of independent living outside of the hospital. In addition, the application could be combined with positioning devices (Chan et al. 2004) to give medical practitioners their patients’ location together with their health vital signs, such as heart rate and body temperature, so that if there are any significant issues, a team of medical experts could respond swiftly.
In a number of these applications, electrocardiography (ECG) is measured, and its related data are transmitted to the medical database via the Internet (Gund et al. 2008) or wireless communications (Pollonini et al. 2012). These data can be used for medical diagnostic purposes (Jeon et al. 2013). In another research (Fortino et al. 2014), ECGaaS system is developed based on the integration of body sensor networks and a Cloud PaaS infrastructure. This system allows monitoring of ECG data not only from the individuals but also from a group of people; therefore, the application can be used in the older adult villages or care houses where physicians need to monitor the healthcare status of a group of people.
Other wearable monitoring applications may track health status parameters such as blood pressure, respiration, peripheral capillary oxygen saturation (SpO2), pulse rate, and heart rate. These data to be collected from sensors can trigger alarms if abnormal situations are detected (Fanucci et al. 2013). They can also support early diagnosis of hypertension and hypotension (Baig and GholamHosseini 2013) based on the continuous monitoring parameters. For congestive heart failure (CHF) patients, vital sign monitoring together with a questionnaire method has been proposed to check patients’ symptoms and send alerts to their healthcare providers if the collected data are out of the range or patients develop critical symptoms (Suh et al. 2011).
Wearable Technologies for Aged Care Monitoring
Another group of wearable and IoT applications concentrate on supporting and promoting self-healthcare management in old adults, in smart home, or in telemedicine to meet the routine and daily healthcare requirements of the older adults (Sharma et al. 2016). Self-healthcare management is focused on the autonomy, engagement, and self-confidence of the older people. It does not necessarily need the involvement of an external caregiver in the delivery (Chiarini et al. 2013). These technologies can help older people to live independently and safely in their homes (Fanucci et al. 2013).
A set of applications in this group focus on medication reminders. As medical adherence is a common challenge among older people, a high number of research studies and applications are focused on medication reminders (Zanjal and Talmale 2016; Jimenez and Torres 2015) and updating new medicine data of patients (Zanjal and Talmale 2016). Some of these applications are smart medication intake monitoring systems. These systems could be used to constantly remind the patients to take their medication and monitor the medicine container to make sure that the medicine is consumed. Through the monitoring sensors, if the patient does not take the medicine, the system can notify the physicians or the patient’s relatives (Airehrour et al. 2018). Also, Parida et al. (2012) proposed a system that tracks patients’ medicine usage. Huang et al. (2014) proposed an intelligent pill box to remind patients to take medication on time. These solutions are useful for older adults who may suffer from dementia. Wearable technologies are also applied to measure patients’ position and identifying their incidences of fall. These applications are appealing for older adults or people with chronic diseases.
The other common application in this category is fall detection; its objective is to detect any abnormalities in the movement pattern that may lead to fall. In this regard, Chuang et al. (2016) have designed a system that detects abnormalities in the movement patterns through the process of sensors. In this system, if any change is detected in the pattern, a notification is sent to an emergency response team. In another study, a system is proposed that real-time accelerometer and gyro meter data are being used to analyze and detect certain activities that may lead to older person fall (Ahmed et al. 2017). The other solution is presented in Cheng et al. (2015) research which is a real-time fall detection system, and it can detect the motion and location of the body. Some systems utilized Microsoft Kinect depth sensor to spot through tracking the movement of patients in the depth frames if a fall is happening (Gasparrini et al. 2014).
These applications provide support for older people to access emergency services swiftly once the wearable devices detect any abnormalities in the monitored data (Darshan and Anandakumar 2015). With the minimal delay, these systems can alert the emergency services about the need for their services. These systems are able to send alerts to patient caregivers, physicians, or relatives in real time when an older adult needs medical attention or hospitalization (Jimenez and Torres 2015). Airehrour et al. (2018) proposed a system that can generate data from the wearable devices and record the data on real-time basis while the device is attached to a patient, so that during any emergencies, it could facilitate the retrieval of a patient’s medical history. Upon receiving the alerts, the medical emergency team can prepare for the clinical treatment, as well as sending situation-aware instructions for providing first aid to be ambulance team (Nguyen et al. 2017).
Jeon et al. (2013) study such a system in which ECG data or the collected data are used to call emergency services if necessary. Also, in a system proposed by Namahoot et al. (2015), emergency telecare shows patients’ location, emergency information, and instructions to help the users. Moreover, one of the applications of the system designed by Basanta et al. (2016) makes emergency calls based on the data gathered from real-time monitoring of activities and health status of the older person.
Wearable technologies can play an important role in rehabilitation processes especially in those with upper extremity rehabilitation such as after a stroke, or spinal cord injury (Wang et al. 2014), common in older adult.
Wearable devices are widely applied in posture tracking and movement monitoring systems that can be integrated into fully functional rehabilitation systems. Such systems monitor patients’ activities. For the older people with heart failure problems, the system suggested by Bisio et al. (2015) can detect any activities perform by the patients. This system is a tele-monitoring system based on a smartphone (Daponte et al. 2013) to track motion of patients undergoing rehabilitation treatments. With two sensor nodes, the system allows to track movements involving the elbow and shoulder and reproduce these movements on real-time 3D representations. Bento et al. (2012) developed a stimulation device that delivers external vibratory stimuli at the ankle joint through a wearable sensor for long-term ambulatory use for stroke patients. Results of the tolerability test indicated that there were no hazards to report and the majority of patients showed increased awareness about the affected side of the body.
In the study conducted by Timmermans et al. (2010), a sensor-based and technology-supported task-oriented arm training (T-TOAT) method with real-world manipulation is illustrated. Wireless sensors containing accelerometers, magnetometers, and gyroscopes are worn in garments on the thorax, upper arm, and lower arm to collect data such as joint range of motion, speed, and jerkiness of movement during exercise. These data are compiled to represent the movements of the patient. Real-time feedback and feedback of results after completing the movement are provided based on the comparison between the received movements of the patient and customized target parameters set by the therapist. Clinical trial results demonstrated that training improved skilled arm-hand performance significantly.
Future Direction of the Research
As the application of wearable technologies and devices in this area is growing day by day, the amount of research in the area is also significantly increasing. Therefore, conducting a consolidated review is required to integrate and compile relevant evidences from multiple reviews (qualitative or quantitative) into one accessible and usable report. Also, it is essential to perform a critical review of the field to reveal weaknesses, contradictions, controversies, and/or inconsistencies (Paré et al. 2015).
The studies reported are all in the pilot study phase; little has been integrated into routine health service delivery. It is a challenging task to develop and test wearable technologies and devices because health applications demand robust solutions, and testing usually requires real human participants, and it isn’t easy to achieve development, testing, and validation in short durations. The technology keeps upgrading, and new solutions are introduced into the market; therefore, the older test results become redundant. Therefore, the future focus needs to be placed on scaling up the pilot studies to real-world implementation of wearable technologies in healthcare system while facing the challenges above.
This entry outlined a number of challenges that healthcare industries are facing with regard to the older adult population and their healthcare requirements. The findings suggest the reduction of disability due to illness will become a key success factor in aged care, and ultimately, this introduces new challenges for aging populations. The new old have expected to live by themselves as long as possible. Since the typical model of family life living together is becoming rare, assisted care options are on the increase. On the contrary, rest homes and retirement villages are expensive options; the aging individuals can continue to live independently with the assistance of wearable technologies.
The applications and implementations of wearable technologies were conducted as a means to address these challenges. The most promising application of wearable technologies for geriatric care is monitoring of various health conditions and human functions. These groups were explained, and for each group, a number of developed or proposed systems were reviewed.
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