Smart technologies and textiles and their potential use and application in the care and support of elderly individuals: A systematic review

2.1 Literature selection process

This review was prepared according to the criteria for systematic reviews of the literature following PRISMA checklist as well as on the basis of a research protocol of RefHunter [19,20,21,22,23]. To avoid potential bias in the search and review of the literature as much as possible, we conducted the review according to a previously formulated protocol [23]. Here, we formulated the overarching research question of the application potential of smart clothing for the care and support of the elderly individuals, which was presented using current studies and specific product examples.

We formulated the selection (inclusion and exclusion) criteria listed in the next paragraphs as well as a search strategy, the following databases were considered for this: ScienceDirect (Elsevier), PubMed, the Cochrane Library, the Institute of Electrical and Electronics Engineers (IEEE Xplore), and Google Scholar. The databases listed were selected primarily because of their size in terms of content and the fact that the literature they contain is largely freely accessible, so that it is possible to reconstruct the data collected without restriction. Furthermore, databases were selected because they deal in particular with medical, technological, and overlapping topics. They were used to search for articles published between January 2000 and February 2023. The following keywords and their combinations were used as search terms: smart textiles, wearable technology, technology acceptance, elderly people, user acceptance, smart shirt, elderly care, smart clothing, vital sign monitoring, and geriatrics. The MeSH terms health services for the aged and smart materials were also used for the search in PubMed (Table 1). To give a concrete view of available products and current developments in addition to the systematic literature review, corresponding manufacturers and products were evaluated by their relevance. For this purpose, the manufacturers’ websites and previously published papers on these products were taken into account. Table 2 provides an overview of current products, including web addresses and scientific references.

The following inclusion and exclusion criteria were developed before the research was undertaken:

Inclusion criteria:

• Publications and articles published between January 2000 and February 2023

• Publications and articles that were written or available in either the English or German.

The period after 2000 was chosen because the development of intelligent textiles only began to become relevant in that year. In 2001, Tao [24] published a review of the developments, materials, and initial products related to intelligent and functional textiles going back to 1965, when a heat-insulating garment was developed by Mavelous and Desy.

The preliminary search (Identification) resulted in a total number of 807 articles. By omitting duplicates and irrelevant abstracts, 211 full-text articles were identified (Eligibility and Screening). After a careful analysis of the content of each reference using respective checklists [25], a final total of 122 articles and competing sources were included in the systematic review. To supplement some further aspects of this work, 47 additional references were used in the elaboration of this article (Inclusion). As shown in Figure 1, a modified PRISMA flow diagram was used to illustrate the selection process [26].

Figure 1

Modified PRISMA flow diagram.

Data were to be collected from the literature sources in the form of: data on relevant references, using not only research literature but also other sources of information (books, websites), data on the most important results and statements of the references with the question of a common intersection, data on already existing example products that could have relevance for answering the research question, data on the type of references using a qualitative, narrative presentation of the studies as well as data on open research questions that can possibly be identified with our work.

Based on the available literature and additional sources, such as manufacturers’ websites and online statistics, we developed a proposal of categories (Figure 2) and a tabular overview (Table 2) of products relevant to our research question. An endnote database (Clarivate, UK) was created and used to prepare and organize the references.

Figure 2

Examples of current approaches to categorize smart wearables.

2.2 Definitions of terms

In the current research literature and manufacturers’ specifications, a variety of definitions are used to determine smart wearable products, and no definitive terms clearly distinguish between current product varieties. Therefore, we use the following terms throughout the article. Smart wearables are a superordinate designation that refers to any device that can be worn on the body but is not implanted into the body. These include smart clothes (as a textile variation) and various other products, such as glasses, watches, measuring devices, wristbands, and headbands. The designation smart clothing (smart textiles, smart clothes, and smart garments were also used) refers to any garment with more advanced technical or technological features that enable the garment to perform new functions. These features may include light-emitting diodes (LED) lighting, heat transfer or storage, signal transmission, and complex sensor functions.

3.1 Origin and current status: the development of intelligent clothing from research to concrete applicability in diverse life situations

In 1999, Gopalsamy et al. described a shirt called the “Georgia Tech Wearable Motherboard™ (GTWM), which was designed to “monitor in a very systematic way the vital signs of humans in an unobtrusive manner.” The GTWM is considered the first smart shirt worldwide. At the time of publication, the researchers focused on durability, wearability, connectivity, and functionality, such as vital sign monitoring and projectile penetration alerts for military purposes [27].

The current literature contains many highly topical developments in the field of intelligent textiles. Some products are already available on the market or are being tested on end users or patients. Many technologies are still in their infancy and require more in-depth research before being deemed suitable for everyday use. Recent years have seen a considerable increase in products and application possibilities. Smart clothing development currently focuses on power supply efficiency, washability despite technology and electronics, mechanical environment, and commercialization (Table 2).

3.2 Overview and categorization of smart wearables and smart clothing: an overview

Existing proposals for categorization and overviews of smart wearables are summarized in Figure 2. It should be emphasized that a standardized classification of smart wearables does not yet exist, but different working groups, such as the International Electrotechnical Commission (IEC), have addressed this issue [28]. The current IEC classification categorizes product types according to their localization in relation to the human body.

In contrast, Cherenack and van Pieterson described smart textiles along their historical development and identified three major categories [29]. The first category closely follows the vision of wearable computing. Materials with a single function were incorporated into textile materials. The second category encompasses various textile manufacturing methods that integrate electronic materials in a more complex way. The most recent and third category includes the latest developments in technologies with complex functionalities that can be implemented and integrated at the fiber level. These functionalities include measuring functions of heart rate (HR), pressure, biochemical and optical sensors, and gas-sensitive nanofibers (e.g., for air-conditioning systems) that are connected to input and output devices.

Teslasuit^®, a smart wearable company based in London in the United Kingdom [30], lists various products in more detail but does not form superordinate or subordinate groups. Seneviratne et al. developed a multilayered structure with three subgroups (accessories, e-textiles, and e-patches), each of which is differentiated into further product types [31].

In most classification proposals, smart clothes are assigned as a subgroup of smart wearables (Figure 2). Smart clothes and textiles can be further subdivided into the existing categorizations shown and described in Figure 3. Stoppa and Chiolerio presented a classification based on the functionality of smart textiles: passive smart textiles only have a sensory function, whereas active smart textiles provide reactive sensing to stimuli. The latest generation, named very smart textiles, can sense, react, and adapt in a more complex way [32].

Figure 3

Current approaches to categorize smart clothes including the authors’ own suggestion.

More recently, Postolache et al. listed various smart garments according to their medical functions and data acquisition capabilities. The classification is based on collectable data such as electrocardiogram (ECG), oxygen saturation, skin temperature, and functions with respect to outgoing data and incoming data or a combination of both [33] (Figure 3).

Taking into account the various currently available categorizations and definitions, we propose a categorization that provides a comprehensive line-up of smart clothing (Figure 3). Our proposal follows the Smart Wearable Categorization of the IEC (Figure 2) and adheres to the classification of electronic textiles, as shown in Figure 4. Five groups of electronic textiles are specified based on different body regions and functions of the respective products. As an example, we outlined the applicability of smart shirts as garments with a wide range of data acquisition, which can be explained by the position of the textile on the torso. Khundaqji et al. also recognized this benefit of anatomic positioning of upper body garments and recently published a review article on this topic [34].

Figure 4

Positioning and categorization of smart wearables, smart clothing, and smart shirts according to the authors.

3.3 Smart wearable textiles, materials, and technologies

In the past 10 years, numerous monographs [35,36,37] and review articles [32,38,39,40,41] dealing with the development, fabrication, and application of smart wearable textiles and recent developments have been published in an organized manner. In the following, we systematically summarized the development techniques and manufacturing processes from fiber to functional element. We tabulated (Table 3) the latest developments and currently used materials and methods for determining relevant health parameters such as bio-potentials, and respiratory, physical, and chemical parameters.

There are a variety of ways to produce smart clothing with different properties and functions: (1) creating textile fibers that have additional functions (e.g., electrical or optical conductivity [42], sensors, or actuator properties), (2) integrating commercial off-the-shelf components such as integrated circuits or LEDs on the textile after manufacturing, (3) intrinsic or surface functionalization of fibers and fabrics, and (4) hybrid approaches that combine both commercial and textile functionalities [29]. The timing of the introduction of smart functionalities along the textile chain depends on the requirements, effort, and quality standards. Ideally, the maximum reliability of functionality, optimal mechanical properties, repeated washability, low-cost production, and high availability can be ensured.

We described the manufacturing processes along the textile production chain. At the top of the textile production chain is fiber and yarn production (Section 3.3.1), followed by two-dimensional (Section 3.3.2) and three-dimensional (Section 3.3.3) textile production, joining (Section 3.3.4), and subsequent functionalization and finishing (Section 3.3.5) [43].

3.4 Smart technologies in health for an elderly population

In 2015, Khosravi and Ghapanchi analyzed 2,035 studies (published between 2000 and 2014) on assistive technologies and identified the technologies’ effectiveness and application potential for older people. Eight key issues in the care of elderly individuals for which assistive technologies might be used were identified: (1) dependent living, (2) dementia, (3) risk of falls, (4) chronic disease, (5) social isolation, (6) depression, (7) poor well-being, and (8) poor medication management. The assistive technologies were categorized into six clusters: (1) robotics, (2) general ICT, (3) sensor technology, (4) telemedicine, (5) medication management applications, and (6) video games [85]. The authors were able to show that some assistive technologies are considerably effective at changing and enhancing the daily lives of elderly individuals.

Ghahremani and Latifi investigated the multidisciplinary environment for e-textiles, consisting of textiles, electrical engineering, and information science. Describing manufacturing processes, materials, system integration, and applications such as public safety, health care, fashion, space exploration, military, sports, and consumer fitness, the authors identified several possible applications of intelligent textiles. The authors propose clinical and monitoring applications for the health care sector in which textiles perform functions as actuators or sensors for communication purposes [86] beyond the typical characteristics of protection and aesthetics.

In the Netherlands, a team from the Department of Industrial Design at Eindhoven University of Technology [87] is investigating the application of smart textiles, including smart clothes, for use in services such as health care, which they termed smart textile services. As an example, developers presented a cardigan that can provide audio feedback that has many properties suitable for everyday use (non-stigmatizing appearance, comfort, and long-term data acquisition). Developers recommended applications in geriatric (e.g., dementia) or rehabilitative (e.g., physiotherapy) environments. Within the holistic approach of “smart housing,” smart wearables are seen by some authors as important components of a complex network for monitoring and caring for elderly individuals [13].

3.5 Smart textiles: product examples and current studies

With the increasing interest in smart textiles, the number of scientific research papers is also growing steadily. Taking into account different focal points, an increasing number of review papers have provided the best possible overview in this research field [71,88,89].

Khoshmanesh et al. focused on three topics (personalized health monitoring, smart gloves and prostheses, and assistive technologies) in the field of textile smart prosthetics and described corresponding prototypes and possible applications [90].

Dulal et al. addressed the sustainability aspect of smart clothing, thus reconciling two major topics moving research [91].

A common focus in the worldwide development of intelligent textiles, especially smart shirts, is electrocardiograms. Some such prototypes are already collecting promising data [92,93,94,95,96,97], and some ECG shirts (such as the one from Xenoma Inc., Japan [98]) have already made the leap into applications in medical diagnostics.

A recent 2019 study reported on the applicability and validity of a smart shirt with a 12-channel ECG function. Two study groups equipped with either an ECG shirt or a standard device were compared over several periods of 3 min each. The collected data showed that the validity and applicability of the smart shirt over the short testing period were reasonable and promising [93]. A similar study using a smart shirt with 12-lead ECG equipment and a smartphone as the end device successfully tested the feasibility of all-day data collection powered by a small coin cell battery within the shirt. In addition, the researchers noted that the material composition was inexpensive and therefore potentially suitable for everyday use [99].

Furthermore, cardiac arrhythmias can be reliably detected by replacing conventional sensors of the body patch type with dry electrodes integrated into textiles while maintaining comparably reliable data acquisition with an accuracy of 98.2 ± 2% [100].

Mansoor Baig et al. provided various possibilities of wearable health monitoring devices with a focus on the recording of ECG data related to older adults; however, substantial drawbacks, such as data security, patient restrictions, short battery life, and a lack of consumer acceptance and medical professional feedback, must be considered for the successful use of the devices [101]. Another recent work described a smart shirt with electromyograph (EMG) measurement function to assess and display muscle fatigue, performance, and muscle activity limits. The system was able to adequately monitor EMG activity and provide valid data for sport applications but has not been evaluated for use in elderly individuals (e.g., to assess frailty) [102].

Other studies [40,103] have evaluated smart clothing in subpopulations, such as elderly people in need of care or nursing. Active ageing with the aid of smart clothing is also gaining increasing attention.

Many prototypes under investigation are providing increasingly valid data. Acceptance by older populations also seems to be achieved, especially since the coming generations will be increasingly familiar with technical devices. Criticism is often leveled at the fact that currently small pilot studies are often still being carried out and there is a lack of large studies. The authors also point out aspects such as data security and striving for the most independent and proactive use of smart clothes possible.

In a literature review, Bravo and Muñoz investigated wearables (also partly non-textile) with regard to their application potential among elderly people, especially in rehabilitation, as well as in consideration of monitoring and safety [104].

Wang et al. examined various technologies, including smart clothes for use in the care of elderly individuals, and named three categories by which the technologies examined were classified: (1) real-time vital sign monitoring, (2) indoor positioning, and (3) activity recognition. Based on their results, the authors recommended an extension of the usual data collection of smart garments. In most cases, such data collection consists of vital sign monitoring and activity or motion capture and should be extended by the “positioning” function for geriatric purposes. The authors found this parameter to be a useful extension because of the increased risk of illness and falls at advanced ages [105]. In Wearable Systems for Health Care Applications published in 2004, wearable systems and related product types were presented in terms of their properties and potential applications in the health care sector. The authors classified wearables as a special form of ubiquitous computing because of their context sensitivity and classified the products according to their areas of application, including surveillance, mobile treatment, assisted living systems, and wearables for medical personnel. One focus of the work was the successful interaction between the respective system, the environment, and the patient. The authors described four characteristics that a product should fulfil for this purpose: (1) seamless integration of the system into the outfit, (2) the ability to react to context information in a meaningful way and without patient interaction, (3) the ability to generate context awareness through sensors, and (4) usability even with low cognitive abilities. If the systems investigated are successfully further developed and used, the results of the research point to a future improvement in the quality and reduction in the costs of care for the elderly population [106].

Other important aspects of successful monitoring of geriatric patients include body posture and activity. These were evaluated by Lin et al., who integrated real-time posture monitoring and emergency warnings into a smart vest. Using the technology acceptance model, the applicability and adoption of this garment was tested in a group of older study participants. The results showed excellent applicability and good acceptance [107].

In the following section, we provide additional product examples of smart clothing (Table 2). Various garments and appliances were selected for their functionality, applicability, and textile properties. They are intended to provide a representative overview of the most recent developments worldwide. All products shown in the table have textile as well as technical functional properties, which serve to acquire data about the respective condition of the user. To provide an exhaustive overview, products that have not yet been specifically designed for older adults and geriatric settings but that may have potential for this group were also selected. The variety of developments ranges from socks to smart bras to full-body clothing. These are competing products in the sports and health sector with (potential) relevance for geriatric settings. Sensoria artificial intelligence sports include, for example, socks with distinct features, such as tracking functions for cadence, force and gait variables, which may also be useful in gerontology [108].

The shirt Hexoskin offers data acquisition and monitoring functions with relevance to the health sector [109,110,111]. The functions of the elastic material include recording capabilities for the following values and vital parameters: cardiac sensors that collect electrocardiogram (ECG) and heart rate (HR) data, respiratory rate intervals and Q-, R- and S-waves event detection, movement sensors that record steps, acceleration and energy expenditure as well as breathing sensors for breathing and respiratory rate, tidal volume (VT), inspiration and expiration events, and related quality assessment channels. Furthermore, functional sleep measurements are also included [16]. The validity of the experimental values, such as HR, breathing rate, VT, minute ventilation, and hip motion intensity, were evaluated compared to standard measurements, which resulted in nonsignificant differences between Hexoskin and the respective “gold standard” [112].

BWell Health Wearware female (X10X) and male (X10Y) shirts meet the respective requirements of the female and male physique and therefore represent two adapted products whose field of application should also correspond to that of the older population. The two different garments have strain gauges for respiration measurement, a total of ten dry electrodes for ECG acquisition and a device for data collection and transmission to a terminal (tablet, computer, or smartphone) or a secure cloud storage. The garments are already certified in Europe (CE) as class IIa medical devices and therefore can be used by physicians for data acquisition and resulting diagnoses.

Teslasuits, consisting of jackets and trousers, accommodate a body haptic feedback system via electrostimulation. These garments are also equipped with an integrated biometric system that measures vital parameters and records body position and movement. The in- and outgoing data can be connected via Bluetooth so that individual scenarios for training and virtual reality can be created. The applicable areas for athletics, enterprise, rehabilitation, and public safety with respective platform features are presented on the manufacturer’s website (Table 2). Applications for older people are conceivable but have not yet been established. Xenoma from Japan developed a combination of shirts and trousers (“e-skin”). The garments are mainly used for real-time motion capture using measurements of the deformation along e-textile sensors [33]. The company developed a so-called printed circuit fabric, which integrates devices and sensors in circuits on the fabric. Various e-skin product types are available. These items include further and individually developable apps, baby monitoring, accident prevention shirts for motor vehicles, ankle bands for sleep improvement, and sleep and lounge pyjamas for the well-being and health monitoring of elderly individuals. Further functions specifically for the health sector and vital sign monitoring are under development. A developer kit offered by Xenoma called e-kin SDK contains sample APIs that identify the information from strain sensors, accelerometers, and gyro sensors. Fourteen strain gauges and a hub in the middle of the chest provide data acquisition and processing. The hub includes a three-axis accelerometer and three-axis gyro sensor as well as a Bluetooth interface, ensuring connectivity to multiple endpoints. This equipment should be the basis for desired developments and new areas of application.

Enflux developed motion capture clothing consisting of shirts and pants. Ten small inertial measurement unit (IMU) motion sensors (small IMUs) with a chest module form the basis of this clothing. Enflux clothing is already available and offers Bluetooth and connectivity for applications such as Blender and Unity. The material, a PES–Spandex blend, is machine washable, and the electronic nodes, whose functionality consists of motion capturing, are removable, making it already user friendly. SmartsuitPro from Rokoko includes 9-DoF IMUs and a hub for connectivity and connecting cables, all built into nylon-based fabric. Adjustable tightening straps are available for individual size adjustment. Connection software is based on Windows and Mac, and the applicable plugins are Unity 5, Unreal Engine or MotionBuilder. In line with this equipment, SmartsuitPro is mainly used for motion capture.

Neuronmocap from Noitom belongs to the same product group as smart clothing for motion capture. The company already offers very small IMUs in its suite, which make it easier for the wearer to perform natural movements with little additional weight. This product is also mainly used in the virtual reality industry and offers application possibilities for athletes and others.

The Center for Functional Fabrics at Drexel University (USA) is developing the smart fabric belly band and baby band. The former is a smart fabric belly band for use during pregnancy to monitor uterine activity and assess foetal well-being. The baby band offers simplified monitoring of the newborn child after delivery and can be used in neonatology, for example. Several research groups are already investigating the applicability of these products [113,114].

The Advanced Robotics Center (Evolution Innovation Lab) at the National University of Singapore is conducting research on soft robotics in health care, especially for rehabilitation and prevention. Here, for example, the fabric-based Soft Robotic Assistive Glove is being developed for use in poststroke rehabilitation [115,116]. Furthermore, the Soft Robotic Sock for ankle rehabilitation can move the ankles of bedridden patients in various spatial directions to support rehabilitative measures [117]. Another product developed by this lab is the ARMAS Shoulder. This is a 2DOF Shoulder Exosleeve for shoulder rehabilitation [118]. Research is also being conducted on a wheelchair with robotic arms that can support physically impaired individuals in their everyday lives and at least partially replace missing bodily functions (especially movements of the upper extremities) [119].

Xu et al. presented in an article the so-called smart sleeve for the detection of (everyday) human body movements. This is a sleeve made of a soft and stretchable textile pressure sensor matrix, which can be attached to common clothing and was successfully tested among 14 subjects in this research work. The corresponding dataset was made publicly available [120].

For monitoring heart rate variability (HRV) as an expression of the regulatory capacity of the autonomic nervous system, the Ambiotex smart shirt was investigated at the German Sport University Cologne. Here, while smart shirts were generally promising, the measurement accuracy of the smart garment studied depended substantially on the intensity of physical exercise and stress. The most accurate data were obtained at rest, while the accuracy decreased under increasing load. There is still potential for improvement with regard to this aspect [121].

An exploratory study in Denmark is currently investigating the OncoSmartShirt for home monitoring of patients during cancer treatment (start of patient inclusion in May 2022). The aim of the project is to explore how wearables and biometric data can be used as part of symptom or side-effect recognition in patients with cancer during treatment to potentially improve the patients’ quality of life [122].

As a successful example in the preventive field, the NEVERMIND System (smart shirt and app) was investigated in a pragmatic, randomized controlled trial involving 425 subjects with different but severe underlying diseases with regard to the development of depressive symptoms over a period of 12 weeks and was shown to be significantly superior to the usual standard care. The subjects who had used the system developed significantly fewer depressive symptoms [123].

Another product example from the rehabilitation sector is the Double Aid (DAid) smart shirt investigated for subacromial pain syndrome, which detects even slight shoulder movements and provides the patient with feedback on the accuracy of the movement, enabling him to correct the movement [124].

In a clinical trial from January 2022, the Tyme Wear smart shirt was examined in comparison to the existing laboratory equivalent Parvo Medics TrueOne 2400 with regard to its data validity in the collection of personalized ventilation thresholds. A certain reliability was shown here, but there was no significant advantage in data acquisition or validity [125].

Avellar et al. developed a photonic smart garment with 30 multiplexed polymer optical fiber sensors combined with AI algorithms, which was evaluated for its ability to classify human activities (standing, sitting, squatting, arms up and down, walking and running). Highly valid data were shown, so the authors proposed the garment for use in health care in the future [126].

Additionally, with the main function of motion capture but potential other functions, such as heart rate (HR) and ECG recording, Bioman ⁺ and other products were elaborated in cooperation between King’s Metal Fiber and AiQ Synertial. AiQ developed Bioman⁺ and presents application scenarios on its website, including for endurance sports such as marathons and cycling as well as ECG monitoring vests for elderly care. More product examples that have thus far been developed and used primarily for athlete monitoring but may also have potential for health monitoring applications are athlete clothes from Vexatec, Athos Training System, and Sensoria Artificial Intelligence Sportswear (Table 2).

It is important to emphasize that many of the smart garments under development (prototypes) are far from being suitable for use as medical devices but show great potential and are already established in private use. Approval for use in health care will include proof of high-quality standards as well as safety and performance requirements that are strictly regulated by law. To give an example, Xenoma Inc. has already received approval for its e-skin in Japan to carry out outpatient long-term ECG measurements, the recordings of which are then evaluated by medical personnel. The costs are already covered by health insurance companies.

3.6 Medical demands

For medical purposes, there are some requirements for intelligent clothing, which partly differ from previous developments and go beyond the requirements of the military, private athletes, and gaming applications. The medical applications are manifold and conceivable; for example, there are applications in obstetrics (child activity in the womb [113]), cardiology (ECG and vital parameter recording, for example, after myocardial infarction or for the detection of cardiac arrhythmias), pneumology (especially breathing signal, pulse oximetry and HR for patients with chronic obstructive pulmonary disease, asthma, sleep apnoea syndrome, and others), pediatrics (neonatology, vital parameter recording, incontinence recording and warning, and temperature measurements), neurology (motion recording, incontinence recording, recording of vital parameters, and EEG, for example, in poststroke rehabilitation [127]), sleep medicine (breath recoding and sleep recording), rehabilitative medicine (recording of movements and vital parameters), and geriatric medicine (holistic patient monitoring with incontinence recording, recording of temperature and vital parameters, falls, sleep, and GPS tracking, for example, for patients living alone or suffering from dementia). For the latter, it is exceptionally important to investigate the right materials for high data validity, wearing comfort, and durability of textiles. Because of the increase in the number of elderly individuals in the population and the resulting additional burden from the care and nursing of this population, the functions already mentioned above could be an important step towards providing adequate assistance in care.

Incontinence, increased frailty, tendency to fall, cognitive loss including dementia, and sleep disorders are among the most common complaints with advanced age. For all these concerns, intelligent clothing can be helpful, for example, by detecting incontinence, tendency to fall or pathological vital parameters and then sounding an alarm. In addition, intelligent clothing could be used to detect sleep disorders, which could save older adults, in particular, from having to undergo a complex sleep laboratory (polysomnography) examination. An important aspect that particularly affects dementia sufferers is loss of orientation. With GPS tracking, it is already possible to determine a location by wearing intelligent clothing, which would also be a conceivable field of application.

In a recent review, Tat et al. provide an update on smart textiles in the two broad contexts of (1) sustainability and (2) personal health care (diagnostic and therapeutic applications, review of recent studies, and listing of examples) [128]. In this and other contributions that address uses in health care, it is postulated that if applicability, sustainability, and data validity are improved and personal rights and data protection are adequately taken into account, smart clothing will be applied in future health care practices [129,130,131,132].

3.7 Technology acceptance by an elderly population

Often, older adults have difficulties learning new things and adapting to new situations. General theories for acceptance as well as approaches specific to elderly individuals have been proposed, such as the Technology Acceptance Model (TAM and TAM2) [133,134], the Elderadopt model [135], the Senior Technology Acceptance Model [2], and Dynamics In Technology Use by Seniors [136]. To understand whether and how older patients deal with these new technologies and developments, several studies have been performed. One of the largest exploratory studies, entitled “Elderly persons’ perception and acceptance of using wireless sensor networks to assist healthcare,” examined attitudes, perceptions, and concerns about new technologies in the health care sector, using wireless sensor network technologies as an example [1]. Sixteen concepts in relation to elderly participants’ perceptions, concerns, and attitudes towards wireless sensor systems were identified by means of focus groups and a literature review including an examination of known models. These concepts were divided into six themes that described the influencing factors relevant to the research question as follows: independence, perceived impact on quality of life, concerns associated with examined technologies, user personal preferences, design preferences, and external factors. In addition, the cost factors and maintaining independence with increasing age were of great value to the respondents. The authors’ findings indicated a generally positive attitude of the study participants towards the investigated technologies. Furthermore, especially in the case of elderly or disabled people, the question of how an ethically adequate inclusion of people as active users of smart textiles can be implemented should be asked. There have already been several studies on this still small field of science. For example, Peine et al. are developing and shaping the new academic field of sociogerontechnology. Here, demographic change towards an ageing world population and technological progress are viewed as overlapping and mutually dependent coevolutionary fields [137]. Another interesting question in terms of technology acceptance is the question of any sex distinction between males and females. There have been scientific studies on this topic for many years, which have produced heterogeneous results. Basically, there are sex differences in behavior when dealing with technologies. Many (meta-)analyses also show that men still have a more positive attitude or a more positive self-perception towards technology use than women. Over the last few years, there has been a reduction in sex differences in the dimensions of affect and self-efficacy, but women still seem to have less conviction about their abilities to use technology. However, according to the studies, there is hardly any difference between the two sexes in terms of goal achievement [138,139].

To complete the content of this work, a rough critical examination of social science issues in the context of smart textiles was also developed. Smart textiles and garments seem to contribute to more comfortable hospital treatments and medical care by making the patient environment more comfortable. This could be a positive contribution to future patient care. Examples of this are the abovementioned baby band and belly band products in the field of obstetrics and neonatology [113].