Intelligent-Healthcare-Oriented 6G Visible Light Communications: A Methodological Review

Abstract

With the exciting and consistent development on radio frequency (RF) based internet of medical things, the relevant investigations and deployments for intelligent healthcare have demonstrated tremendous economic and social value. Simultaneously, for filling the gap of the secure and green transmission level of the RF based intelligent healthcare technologies in the future 6G era, increasing scholars are aggressively introducing visible light communications (VLC) into the intelligent healthcare community, and have achieved a series of impressive research advancements. For presenting the cutting-edge progress of VLC applications in intelligent healthcare and internet of medical things via one comprehensive style, this work overviews and discusses the intelligent healthcare oriented VLC in relevant branch domains including VLC-enabled healthcare transmission techniques, VLC-enabled healthcare positioning techniques, VLC-enabled healthcare artificial intelligence techniques, and VLC-enabled healthcare implementation techniques. At last, this work summarizes the potential challenges and research opportunities to sustainably develop the intelligent healthcare oriented VLC technology in the upcoming 6G and beyond era.

Graphical abstract

Keywords

visible light communications / intelligent healthcare / 6G / optical wireless communications / internet of medical things / visible light positioning

Introduction

The innovative intelligent healthcare is becoming increasingly popular in the diverse medical applications[1–4]. Nevertheless, current radio frequency (RF) based intelligent healthcare paradigm has to face a series of intractable challenges, for instance, the shortage of spectrum resource, capacity, and confidentiality. Unlike the well-known RF technology paradigm, visible light communications (VLC) is able to offer numerous inherent advantages, including unregulated and abundant light spectrum resource, natural immunity to the conventional electromagnetic interference, and higher security performance[5–8]. Therefore, for addressing the mentioned issues in the RF based intelligent healthcare, unprecedented worldwide researchers with interdisciplinary academic background actively engage in the exploration of utilizing customized VLC schemes in order to precisely enhancing the key performance of intelligent healthcare services[9–11].

In reality, up to now, VLC and related designs have been positively introduced in main branch directions of the intelligent healthcare and internet of medical things community[12–16], including but not limited to the healthcare biomedical data transmission[17–20], healthcare backscattering connections[21–23], healthcare hybrid communication[24–26], healthcare device positioning[27–31], healthcare artificial intelligence[32–35], and healthcare system implementation[36–44]. But, it must be noted that these numerous disorganized reports or articles could not provide one overview of the latest development of intelligent healthcare-oriented VLC techniques. Unfortunately, this absence limits the satisfying propagation and extension of VLC techniques in intelligent healthcare domain, and is against the green and consistent development of intelligent healthcare in the 6G era. For mitigating this issue, this work overviews the latest advances of VLC involved in intelligent healthcare and internet of medical things via a systematic manner, and then analyses the customized VLC in representative branch domains of intelligent healthcare typically including healthcare biomedical transmission, healthcare backscattering transmission, healthcare hybrid transmission, healthcare positioning, healthcare artificial intelligence and healthcare prototype implementation. Finally, this work summarizes the potential research directions to sustainably develop the intelligent healthcare oriented VLC technology in the upcoming 6G era.

Visible light communications-enabled healthcare transmission techniques

As a matter of fact, the emerging VLC-enabled healthcare transmission and its branch domain are highly relied on light emitting diode (LED) light sources and relevant illumination infrastructures, with special emphasis on the application scenarios of healthcare biomedical transmission, healthcare backscattering transmission and healthcare hybrid transmission[45–48]. In view of that all the above novel applications are expected to face ever-increasing spectrum depletion and electromagnetic interference of the envisioned future healthcare 6G ecosystem, the tremendous enhancement of performance level could be derived by introducing customized medical VLC empowering to these diverse healthcare transmission services[49–51].

VLC-enabled healthcare biomedical transmission techniques

Specifically, in this subsection, we mainly research the representative advances of VLC-enabled healthcare biomedical transmission techniques. Up to now, VLC empowering has been introduced to the healthcare biomedical transmission research from several main directions[52–54], including but not limited to Smart Body Area Network (SmartBAN) architecture for healthcare VLC[14], Neonatal Intensive Care Units (NICU) based on VLC[15], VLC system for transmitting analogue physiological signals[17], and electroencephalograph monitoring system based on VLC[19].

With the main aim at avoiding human health hazard and electromagnetic interference with expensive medical instruments, Cheong et al.[17] provided one novel hazardless biomedical sensing data transmission technology using VLC, as shown in Figure 1a. Specifically, the pre-installed white LED lamps are utilized as light information emitters, on off keying modulation is adopted to modulate the biomedical data onto the LED light beams, and Positive-Intrinsic-Negative (PIN) photodiode works as the receiver in this system. The reported experimental results verify that the proposed healthcare VLC system could provide transmission data rate of 56 kbps and bit error rate (BER) of 10^–6 without need of collimating lends, which is accordance with the analogue biomedical electrocardiograph (ECG) signals, and the Health Level Seven (HL7) standard protocol.

At the same time, the study by Salvi et al.[18] focuses on the integration of VLC in healthcare internet of things (IoT), as shown in Figure 1b. Particularly, it is also highlighted that the transformative role of VLC in healthcare IoT, providing energy efficient, interference-free, and secure communications for real-time medical data transmission and patient monitoring.

As for the standardization activities of healthcare VLC, Caputo et al.[14] explored the integration of VLC technologies in European Telecommunication Standards Institute (ETSI) SmartBAN architecture for offering promising solutions in ensuring secure communication and efficient data transmission within RF-free environments. In addition, in this work, Out-of-Body communications and In-Body to On-Body communications, as two particular use cases of VLC in ETSI SmartBAN architecture are comparatively analyzed for paving the way for more effective and personalized healthcare solutions.

Particularly, motivated by the need of reliable transmission for vital signs of babies in the NICU, Niranga et al.[15] explored the design and architecture of a VLC system, NeoCommLight for RF-restricted NICUs. Specifically, by the relevant prototype results, it is identified that transmission data rate of 800 kbps could to implemented with the maximum distance of 2 m. For clarity, the critical literature review of VLC-enabled healthcare biomedical transmission could be summarized in Table 1.

VLC-enabled healthcare backscattering transmission techniques

In this subsection, we mainly investigate the representative advances of VLC-enabled healthcare backscattering transmission techniques, especially the relevant vehicle-mounted articles. Recently, VLC empowering has been introduced to the healthcare backscattering transmission research from several main directions[21–23], including but not limited to visible light backscattering system for energy harvesting, models of healthcare visible light backscattering communications systems, and VLC-enabled healthcare monitoring.

The VLC-enabled backscattering is becoming one promising technology to support battery-free healthcare IoT nodes. In the work of Qaragoez et al.[21], by combing backscattering and energy-harvesting of VLC&RF, one hybrid communication and energy-harvesting system is proposed to enable battery-free healthcare IoT with positioning capability, as shown in Figure 2a. Accordingly, the numerical results illustrate that this system could achieve RF power harvesting of 16.73 μW and 1 Mbps downlink. Simultaneously, 35 kHz optical channel deliver and 550 μW optical energy harvesting are verified as well.

Currently, bi-directional communication between sensor tag and LED is becoming one promising direction of research for e-Health applications. In Ullah’s study[22], the optical backscattering is introduced to perform indoors bi-directional VLC in hospital environments. In particular, Ullah et al.[22] presented one theoretical end-to-end performance analysis in terms of bit error ratio accounting the main sources of noise and physical parameters, and the system parameters impact on the backscattering information transfer process is evaluated as well. And the envisioned point-to-point link for visible light backscattering communication is shown in Figure 2b.

For clarity, the critical literature review of VLC-enabled healthcare backscattering transmission could be summarized in Table 2.

VLC-enabled healthcare hybrid transmission techniques

In this subsection, we focus on the representative advances of VLC-enabled healthcare hybrid transmission techniques. Actually, VLC empowering has been introduced to the healthcare hybrid transmission research from several main directions, including but not limited to hybrid RF and optical wireless communication (RF-OWC) body area networks[24], and authentication platform integrating RF and VLC[26].

Apparently, due to the potential security challenges introduced by integrating communication and sensing capability to hybrid wireless body area network, it is quite challenging for ensuring sufficient secrecy energy efficiency simultaneously. For quantifying the trade-off between the energy consumption and secure communication, through the lens of secrecy energy efficiency, Soderi S and Zappone A presented[24] one novel framework for quantifying and optimizing secure transmission in hybrid RF-optical wireless communication networks, as shown in Figure 3. The reported numerical results demonstrates that approximately 3.5 b/Hz/Joule secrecy energy efficiency could be achieved by optimization on hybrid mode, which provides one robust foundation for designing 6G low power healthcare communication systems.

In term of improving authentication mechanisms, Maggioni et al.[26] proposed one hybrid authentication framework which integrates VLC and RF to enhance security in medical information and communication technologies, with special emphasis on resource-limited environments. By utilizing the complementary properties of VLC and RF links, one robust authentication mechanism could be provided to mitigate spoofing, jamming, and replay attacks, while seamless and efficient access control could be ensured for the healthcare networks. Furthermore, it is identified that this scheme could maintain secure communication by dynamically adapting transmission and authentication parameters.

For clarity, the critical literature review of VLC-enabled healthcare hybrid transmission techniques could be summarized in Table 3.

Visible light communications-enabled healthcare positioning techniques

In this section, we mainly discuss the representative advances of VLC-enabled healthcare positioning techniques. Actually, VLC empowering has been introduced to the healthcare positioning research from several main directions, including but not limited to hybrid VLC/PLC positioning system[28], visible light localization using multi-colour fingerprinting[29], and physiological monitoring system using VLC localization[31].

Recently, thanks to the increased demand for location aware medical services, healthcare positioning systems are gaining increasing attention. Tremendous attention has been paid to the VLC-enabled healthcare positioning systems, considering their superior positioning accuracy, low energy consumption and immunity to electromagnetic interference. In Viera Riquelme’s study[31], for COVID-19 patients, one VLC-based an optimized localization and physiological monitoring system is proposed. Accordingly, this proposed system could balance computational efficiency and localization accuracy while enabling the real-time monitoring of vital physiological indicators. For optimizing the localization performance, the particle swarm optimization is utilized to improve positioning accuracy, while the best trade-off between computational cost and precision could be achieved by applying 700 to 1,100 particles. And this envisioned physiological monitoring system for COVID-19 is shown in Figure 4a.

In term of feasibility demonstration of VLC-based healthcare localization, Rexhausen et al.[29] built one novel indoor healthcare localization system using multi-colour fingerprinting, as shown in Figure 4b. Accordingly, one low-cost experiment setup is designed to evaluate the localization error of this healthcare system. The obtained results illustrate that localization accuracy of about 10 cm could be achieved on average by using involved multi-colour fingerprinting and distinct machine learning methods.

As for the left all-optical healthcare tracking system, Lang et al.[28] implemented one integrated design of received signal strength (RSS) based hybrid power line communication and VLC indoor positioning system. And this system consists of existing power wiring in one building, user end optical tags, and host LED ulbs. It is demonstrated that the centimetre tracking accuracy could be realized by applying RSS triangular positioning algorithm in this system, which contributes to the modernization of next-generation intelligent healthcare systems.

For clarity, the critical literature review of VLC-enabled healthcare positioning techniques could be summarized in Table 4.

Visible light communications-enabled healthcare artificial intelligence techniques

In this section, we summarize the main advance of VLC-enabled healthcare artificial intelligence techniques from the views of VLC-based passive posture monitoring[32], transmission architecture based on VLC and hybrid machine learning[33], and robot-assisted multiple patient monitoring architecture[34], separately.

Note that the growth of maintaining wellness without disrupting daily routines, indoor health monitoring propelled the need for privacy-preserving, non-intrusive solution. Nevertheless, the conventional health monitoring methods must face multiple challenges, including inconvenient wearability, privacy concerns, and susceptibility to RF interference. For addressing this issue, Li et al.[32] proposed one indoor health monitoring system with VLC-based passive posture detection, as shown in Figure 5a. Moreover, several machine learning model are customized designed to analyze VLC signals captured by the optical receivers. The needed high computational efficiency and predication accuracy are ensured by these models, which are vital for real-time monitoring applications and edge computing. And results demonstrate that this system is capable of detect different human postures with accuracy rate exceeding 90%.

In term of healthcare transmission architecture, Sasirekha and Senthil Kumar[33] detailed the novel integrating VLC and hybrid machine learning methods, as shown in Figure 5b. By numerical simulation, it is identified that the energy consumption, packet delivery ratio, and average latency of this proposed model is better than the counterparts of the RF-based model and other intelligent wireless sensor network models.

At the same time, for providing low latency and reliable eHealth solutions, Chowdhury et al.[34] proposed one optical camera communication (OCC) based monitoring system. In particular, the related design paradigm exploits reliable fifth-generation eHealth solutions for monitoring patients in ambulances, outdoors, and intensive care units. Accordingly, in this proposed system, the various medical parameters are sensed by skin-type patch sensor, and these medical parameters are converted to electrical signals by the transducer. And then the signals are digitalized and transmitted by the LED or LED array through optical frequency band. Finally, cameras are utilized as OCC receiver to capture the optical frequency signal.

For clarity, the critical literature review of VLC-enabled healthcare artificial intelligence techniques could be summarized in Table 5.

Visible light communications-enabled healthcare implementation techniques

In this section, the main advance of VLC-enabled healthcare implementation techniques includes but not limited to system-on-chip solution for smart hospitals, telemedicine system using VLC, and clinical devices using VLC[36–44], separately.

For developing smart hospital operations, the VLC based wireless tracking of asset and personal is arisen for hospitals where concerned RF interference hazards are strictly limited. As for the prototype implementation of VLC smart hospitals tracking system, Pan et al.[37] presented one system-on-chip solution for smart hospitals based on existing LED lighting infrastructure. One commercial 45 nm complementary metal-oxide-semiconductor (CMOS) transistor integrated circuit technology is adopted to design the system-on-chip transceiver for this prototype VLC system. And by system and measurements, it is verified that tracking resolution of cm level could be achieved, and the feasibility of future VLC e-health application is confirmed as well.

In term of telemedicine system of medical body area networks (MBAN), Ezilarasan et al.[38] presented one experimental setup of telemedicine system using VLC and PIC16F877A microcontroller. And experimental results illustrate that without requiring complex installations, this prototype could provide secure data communication and adequate lighting simultaneously. In particular, the liquid crystal display (LCD) of this setup is used to display the output while one auditory signal is applied to alert the caregivers about the respiration and heart rate monitoring of the patients.

As for the left risk assessment of electromagnetic interference, Ontiveros et al.[42] proposed the VLC scheme as one electromagnetic interference-immune alternative for medical data transmission. The proposed VLC is experimental evaluated under electromagnetic interference condition, and the emitted VLC signal is passed through one achromatic doublet lens to focus the beam footprint onto the photo detector of the receiver. Specifically, despite the presence of the residual RF emissions and ambient lighting, no disturbances or communication are found and dropouts while high signal quality could be indicated by the measured signal to noise of 25.05 dB and measured error vector magnitude of 3.65%.

For clarity, the critical literature review of VLC-enabled healthcare implementation techniques could be summarized in Table 6.

Future research opportunities and challenges

Although the above impressive achievements have been made in the emerging domain of intelligent healthcare oriented 6G VLC, it must be noted that many limitations, challenges of intelligent healthcare oriented 6G VLC must be carefully studied and addressed, which mainly include that random device orientation, constrained receiver field of view, light link blockage, shortage of mobility support, and limited LED modulation bandwidth. For addressing these main challenges, a series of distinct branch directions of intelligent healthcare VLC family are waiting for the introducing and application of the customized techniques[55–59]. As the potential and fundamental near future studies, the recommended branch directions includes but not limited to optical beam predictions for healthcare VLC, optical beam search and recovery for healthcare VLC, hybrid Terahertz and healthcare VLC, uniform lighting generation for healthcare VLC and so on. It must be noted that, the novel non-Lambertian light beam could provide commercially available and distinct light radiation patterns characteristics, typically as shown in Figure 6, which objectively provides abundant research opportunities of utilizing light beam dimension for the cutting-edge intelligent healthcare VLC. Following the work of Kaljun and Žerovnik, for convenience, the respective spatial radiation intensity of C13353 non-Lambertian light beam pattern could be profiled by one sum of cosine functions[60]:

\begin{array}{}\text{(1)}& I\left(\theta \right)={\displaystyle \sum _i{a}_i\ast \cos {\left(\theta -b_i\right)}^{c_i}}\end{array}

where the coefficient values of cosine functions for C13353 non-Lambertian light beam pattern are identified as a₁ = 1.0000, b₁ = –6.5697°, c₁ = 3.5295, a₂ = 0.07883, b₂ = 64.1715°, c₂ = 27.7455, a₃ = 0.17075, b₃ = 30.8478°, and c₃ = 100.0000[60]. Correspondingly, for the future OWN, the 2D and 3D representation of this C13353 non-Lambertian optical beam from the work of David Kaljun are shown in Figure 6a.

Following the work of Kaljun and Žerovnik, for convenience, for the CA11934 non-Lambertian light beam of OWN, the spatial radiation intensity could be profiled by Equation (1) as well. But the relevant coefficient values of cosine functions must be renewed as followings: a₁ = 0.84767, b₁ = –11.4000°, c₁ = 5.7865, a₂ = 0.32803, b₂ = 9.6213°, c₂ = 37.2890, a₃ = 0.29591, b₃ = –13.5748°, and c₃ = 56.1519[60]. Correspondingly, for the future OWN, the 2D and 3D representation of CA11934 non-Lambertian optical beam from the work of David Kaljun are shown in Figure 6b.

It could be anticipated that, for the above valuable research directions, the significant performance gains could be derived in terms of security, flexibility, robustness, transmission efficiency via the customized solutions for intelligent healthcare VLC.

Conclusion

This paper aims at providing one thorough and latest survey on in intelligent healthcare oriented 6G VLC techniques for the upcoming 6G and beyond era. Start with the discussion from the state-of-the-art of the intelligent healthcare oriented VLC techniques, this paper summarizes the most relevant advances in the healthcare biomedical transmission, healthcare backscattering transmission and healthcare hybrid transmission aspects of the VLC community. Then, the representative systems and designs are comparatively investigated for the VLC-enabled healthcare positioning techniques. Moreover, the rapidly growing solutions and methodologies of VLC-enabled healthcare artificial intelligence techniques and VLC-enabled healthcare implementation techniques are also presented in terms of distinct aspects, followed by the key discussion on potential challenges and research opportunities for the intelligent healthcare oriented VLC in the more intelligent 6G and beyond era.

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