Innovative IoT Solutions and Wearable Sensing Systems for Monitoring Human Biophysical Parameters: A Review
Abstract
:1. Introduction
- A comprehensive overview of recent advances in sensing technologies to monitor the biophysical parameters suitable for integration into wearable and portable devices; specifically, we focused on advanced techniques for monitoring HR, BP, respiration rate (RR), blood glucose level and others, in a non-invasive or even contactless way. In addition, wearable applications involving Galvanic Skin Response (GSR) measurements are discussed, a standard indicator of the physical or psychological conditions, for predicting epileptic seizures [22], diagnosing bipolar dysfunction [23], and detecting sleepiness [24]. We investigated the application of sweat sensors for rapid and non-invasive detection of toxins, drugs, hormones, alcohol, and glucose level [25].
- An overview of the IoT systems for health monitoring applications, focusing on the different IoT architectures and supported services. Analyzed systems make heavy use of wearable devices for high-resolution detection of the patient parameters, along with edge/fog computing to limit their requirements in terms of computational resources, power consumption, and energy autonomy [26]. Furthermore, cloud computing allows integrated management, and processing and storing of acquired data can be carried out. In this context, Artificial Intelligence (AI) and Machine Learning (ML) techniques can be integrated into their supported services to simplify the handling of a massive data amount and to infer useful information from them [27]. Finally, IoT frameworks for gait and life-quality monitoring are discussed, focusing on IoT systems for remote fall detection, based on wearable devices and ML techniques [28].
2. Overview of Innovative Sensing Systems and Algorithms for Monitoring Biophysical Parameters
- Forearm in dry condition;
- Forearm with applied a skin lotion to increase the hydration level;
- Forearm wet with water;
- Forearm dried to remove lotion and water residues.
- Whole-body washdown technique: It is the main technique to determine electrolyte loss since the outflow sweat is collected, and evaporative sweating is undisturbed;
- Patches: Consisting of a hydrophilic and porous structure placed between the skin and an external membrane. It is applied to the forearm, thigh, back, and calf;
- Polymer bags/films: A polyethene sheet with a thin layer of petroleum jelly and paraffin oil on the skin is used as an anaerobic sweat collector to gather large sweat volumes with less contamination and evaporative water loss;
- Macroducts: Plastic capsule placed on the skin with spiral plastic tube collecting sweat, avoiding sweat loss, contamination, and potential hydromeiosis.
3. Overview on IoT Systems for Health Monitoring Applications: Architecture Point of View and Supported Services
- Ambient Assisted Living (AAL), an IoT platform that assists elderly and disabled people thanks to AI techniques for extending and improving their life;
- Internet of m-health things (m-IoT), that consists of mobile computing, medicals sensors, and communication technologies for healthcare services;
- IoT-based Adverse Drug Reaction (ADR), that allows a patient to find a specific solution, according to his allergy profile and electronic health record, for an injury caused by the medicine of assumption;
- Community Healthcare (CH), an IoT-based network that covers an area surrounding a local community to access remote medical advice and health data;
- Children Health Information (CHI) that helps children with behavioral or mental problems by educating and amusing them;
- Wearable Device Access (WDA) that allows remote monitoring of a patient by using non-intrusive sensors equipping mobile computing devices like smartphones;
- Semantic Medical Access (SMA) for sharing medical knowledge and information by using semantics and ontologies;
- Indirect Emergency Healthcare (IEH) that suggests the behavior in dangerous situations like road accidents or adverse weather conditions;
- Embedded Gateway Configuration (EGC), an architectural service that links the Internet and medical devices to the network nodes to which patients are connected;
- Embedded Context Prediction (ECP), a generic framework with a suitable mechanism to create context-aware healthcare applications.
- Glucose level sensing that helps planning meals, activities, and medication by revealing the blood glucose level of patients affected by diabetes;
- Electrocardiogram monitoring to eventually diagnose heart diseases such as arrhythmias and myocardial ischemia by detecting the heart electrical activity;
- Monitoring of blood pressure and body temperature, by using suitable sensors, crucial parameters for healthcare services;
- Oxygen saturation monitoring, useful for technology-driven medical healthcare applications, obtained by combining pulse oximetry with IoT;
- Rehabilitation system for improving the rehabilitation of people with physical impairment or disability;
- Medication management, that offers several solutions to the non-fulfilment problem in medication, representing a severe menace for public health;
- Wheelchair management, that offers an automatic wheelchair to disabled people;
- Imminent healthcare solutions, that allows numerous portable medical devices to be integrated with IoT networks;
- Healthcare solutions using smartphones, exploiting smartphone functionalities to control electronic devices extending its capabilities in the IoT platform.
4. Conclusions
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Work | Edge/Fog Computing | Storage Modality | Feedback Typology |
---|---|---|---|
C. Kan et al. [69] | Smartphone provided pre-processing capability and network connectivity | Central DB | Prediction about heart diseases |
E. Spanò et al. [70] | Gateway collected and processed data from wearables devices | Central DB | Information about heart dysfunctions |
H. Moustafa et al. [71] | Edge Cloud of Gateway performed data aggregation from wearable devices | Local and Central DB | Information about health and wellness of user’s status |
M. Chen et al. [72] | Local Health providers | Central DB | Emergency medical aid |
Medical advisor | |||
Warning to family members | |||
A.M. Rahmani et al. [73] | Gateways carried out data processing, local notification, protocol conversion, data filtering and mining | Local and Central DB | Emergency medical aid |
Medical advisor | |||
Warning to family members | |||
B. Farahani et al. [74] | Fog nodes provided network connectivity, computational power and storage | Local and Central DB | Emergency medical aid |
Medical advisor | |||
Warning to family members | |||
A. Rashed et al. [76] | Gateways carried out data processing, local notification, protocol conversion | Local and Central DB | Medical advisor |
Information about health and wellness of user’s status | |||
S. Green et al. [89] | - | Local and Central DB | Fall Detection, Warning messages to family and caregivers |
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De Fazio, R.; De Vittorio, M.; Visconti, P. Innovative IoT Solutions and Wearable Sensing Systems for Monitoring Human Biophysical Parameters: A Review. Electronics 2021, 10, 1660. https://doi.org/10.3390/electronics10141660
De Fazio R, De Vittorio M, Visconti P. Innovative IoT Solutions and Wearable Sensing Systems for Monitoring Human Biophysical Parameters: A Review. Electronics. 2021; 10(14):1660. https://doi.org/10.3390/electronics10141660
Chicago/Turabian StyleDe Fazio, Roberto, Massimo De Vittorio, and Paolo Visconti. 2021. "Innovative IoT Solutions and Wearable Sensing Systems for Monitoring Human Biophysical Parameters: A Review" Electronics 10, no. 14: 1660. https://doi.org/10.3390/electronics10141660