Giovanni Saggio

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Verified

Giovanni verified their affiliation via an institutional email.

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• Ph.D.
• Professor at University of Rome Tor Vergata

Background Reduced arm swing movements during gait are an early motor manifestation of Parkinson’s disease (PD). The clinical evolution, response to L-Dopa and pathophysiological underpinning of abnormal arm swing movements in PD remain largely unclear. By using a network of wearable sensors, this study objectively assesses arm swing movements duri...

Background: This paper aims to complement the latest contribution in the literature that provides estimates of physiological parameters of a dynamic model for the elbow time profile during walking while linking them to a neurodegenerative disorder (Parkinsons’s disease) characterized by motor symptoms. An upper limb model is here proposed in which...

Detecting potential alcohol inebriation or intoxication status holds paramount significance for social prevention and security. Beyond its association with long-term health effects, alcohol consumption can lead to immediate consequences, including reduced control over one’s actions, with traffic fatalities representing one of the most tragic outcom...

Active life monitoring via chemosensitive sensors could hold promise for enhancing athlete monitoring, training optimization, and performance in athletes. The present work investigates a resistive flex sensor (RFS) in the guise of a chemical sensor. Its carbon ‘texture’ has shown to be sensitive to CO2, O2, and RH changes; moreover, different bendi...

Current technologies allow acquiring whatever amount of data (even big data), from whatever system (object, component, mechanism, network, implant, machinery, structure, asset, etc.), during whatever time lapse (secs, hours, weeks, years). Therefore, potentially it is possible to fully characterize any system for any time we need, with the possible...

In recent years, the boost in the development of hardware and software resources for building virtual reality environments has fuelled the development of tools to support training in different disciplines. The purpose of this work is to discuss a complete methodology and the supporting algorithms to develop a virtual reality environment to train th...

Introduction Deep brain stimulation of the subthalamic nucleus (STN-DBS) can exert relevant effects on the voice of patients with Parkinson's disease (PD). In this study, we used artificial intelligence to objectively analyze the voices of PD patients with STN-DBS. Materials and methods In a cross-sectional study, we enrolled 108 controls and 101...

Parkinson’s disease (PD) is a chronic neurodegenerative disorder with high worldwide prevalence that manifests with muscle rigidity, tremor, postural instability, and slowness of movement. These motor symptoms are mainly evaluated by clinicians via direct observations of patients and, as such, can potentially be influenced by personal biases and in...

Parkinson’s Disease and Adductor-type Spasmodic Dysphonia are two neurological disorders that greatly decrease the quality of life of millions of patients worldwide. Despite this great diffusion, the related diagnoses are often performed empirically, while it could be relevant to count on objective measurable biomarkers, among which researchers hav...

Background Stuttering is a childhood-onset neurodevelopmental disorder affecting speech fluency. The diagnosis and clinical management of stuttering is currently based on perceptual examination and clinical scales. Standardized techniques for acoustic analysis have prompted promising results for the objective assessment of dysfluency in people with...

Introduction The analysis of vocal samples from patients with Parkinson's disease (PDP) can be relevant in supporting early diagnosis and disease monitoring. Intriguingly, speech analysis embeds several complexities influenced by speaker characteristics (e.g., gender and language) and recording conditions (e.g., professional microphones or smartpho...

Parkinson’s Disease (PD) is one of the most common non-curable neurodegenerative diseases. Diagnosis is achieved clinically on the basis of different symptoms with considerable delays from the onset of neurodegenerative processes in the central nervous system. In this study, we investigated early and full-blown PD patients based on the analysis of...

Parkinson’s disease (PD) is responsible for a broad spectrum of signs and symptoms, including relevant motor impairments generally rated by clinical experts. In recent years, motor measurements gathered by technology-based systems have been used more and more to provide objective data. In particular, wearable devices have been adopted to evidence d...

Sensory gloves are devices capable of measuring finger movements and are useful in numerous applications, many of which require real-time data acquisition. However, the procedures explored in the literature to assess measurement repeatability and reliability mainly rely on static or quasi-static conditions. To overcome this limitation, here we prop...

Sensory gloves convert hand postures and movements of fingers into electric signals. Different technologies can be adopted to achieve this conversion, and different approaches can be used to evaluate its effectiveness. In this study, we adopted two types of sensory gloves based on two types of sensors, namely the Resistive Flex Sensor (RFS) and the...

Alongside the currently used nasal swab testing, the COVID-19 pandemic situation would gain noticeable advantages from low-cost tests that are available at any-time, anywhere, at a large-scale, and with real time answers. A novel approach for COVID-19 assessment is adopted here, discriminating negative subjects versus positive or recovered subjects...

We designed, developed and validated a bone conduction-based hand pose sensing wireless and wearable system, capable of distinguishing different hand gestures and enabling the evaluation of the pose angles of the fingers. The system can be used as a valuable alternative to sensory gloves, image processing or electromyographic signal analysis. BCHS...

We proposed and addressed methods for using multiple energy harvesting strategies to power a wearable sensory glove. The capabilities of piezoelectric and thermal energy harvesters were reported, with hand motions and body heat used to these goals. A potential multi-input single-output DC-DC architecture was proposed to harvest energy from the two...

We implemented a Bluetooth Low Energy system concerning the acquisition, encryption, wireless transmission, and reconstruction of the electromyographic signal for prosthetic control. The system is expandable with other devices supporting Bluetooth and is a valuable alternative to the current proprietary implantable EMG systems, which use restricted...

We designed, fabricated, and validated a piezoresistive bending sensor, a fundamental component of wearable electronic devices for monitoring human motion. The most diffused opaque carbon-based resistance flex sensors suffer from low detection for small bending angles. The sensor we here present is based on a semi-transparent active material (fulle...

We designed, fabricated, and tested a UHF RFID-based wireless system for electromyographic sensing, differently from the usual RFID employment on TAGs. The design leads to a fully integrated system, not electromagnetically interfering with the analogic part of the board, thus preserving the very low signal coming from the electromyographic activity...

Background. It has been shown in the very recent literature that human walking generates rhythmic motor patterns with hidden time harmonic structures that are represented (at the subject’s comfortable speed) by the occurrence of the golden ratio as the the ratio of the durations of specific walking gait subphases. Such harmonic proportions may be a...

Objective: In order to evaluate Parkinson disease patients response to therapeutic interventions, sources of information are mainly patient reports and clinicians assessment of motor functions. However, these sources can suffer from patients subjectivity and from inter/intra raters score variability. Our work aimed at determining the impact of wea...

Introduction Parkinson's disease (PD) is characterized by specific voice disorders collectively termed hypokinetic dysarthria. We here investigated voice changes by using machine learning algorithms, in a large cohort of patients with PD in different stages of the disease, OFF and ON therapy. Methods We investigated 115 patients affected by PD (me...

Arm-and-hand tracking by technological means allows gathering data that can be elaborated for determining gesture meaning. To this aim, machine learning (ML) algorithms have been mostly investigated looking for a balance between the highest recognition rate and the lowest recognition time. However, this balance comes mainly from statistical models,...

This work aims to provide details on the latest technological developments regarding LiDAR (Light Imaging Detection And Ranging) systems, with particular reference to the techniques, architectures, and methodologies partially or entirely implemented by means of the FPGA (Field Programmable Gate Array) environment. Currently, LiDAR technology is con...

Many virological tests have been implemented during the COVID-19 pandemic for diagnostic purposes, but they appear unsuitable for screening purposes. Furthermore, current screening strategies are not accurate enough to effectively curb the spread of the disease. Therefore, the present study was conducted within a controlled clinical environment to...

Wireless communication with Implantable Medical Devices (IMDs) based on Radiofrequency Identification in the UHF band suffers from the constraints on the maximum power absorbed by the body tissues. Accordingly, an interrogating antenna placed onto the skin is capable to monitor only a limited region just below its footprint. In some applications li...

Early noninvasive reliable biomarkers are among the major unmet needs in Parkinson's disease (PD) to monitor therapy response and disease progression. Objective measures of motor performances could allow phenotyping of subtle, undetectable, early stage motor impairments of PD patients. This work aims at identifying prognostic biomarkers in newly di...

Healthy and pathological human walking are here interpreted, from a temporal point of view, by means of dynamics-on-graph concepts and generalized finite-length Fibonacci sequences. Such sequences, in their most general definition, concern two sets of eight specific time intervals for the newly defined composite gait cycle, which involves two speci...

We realized and tested a novel system aimed at discriminating different hand poses by means of an active actuating and sensing approach realized by converting electromagnetic-to-mechanical waves (and vice-versa) and analyzing the characteristics of the waves after their travel through the bones and cartilage of the hand. The actuating part is reali...

This study compares the simultaneous measurements of finger joint angles obtained with a myoelectric armband (Myo), composed of eight surface electromyography (sEMG) sensors mounted on an elastic support, and a data glove, equipped with ten flex sensor on metacarpal and proximal finger joints. The flexion angles of all finger joints in four hand po...

Myotonic dystrophy type 1 (DM1) is a genetic inherited autosomal dominant disease characterized by multisystem involvement, including muscle, heart, brain, eye, and endocrine system. Although several methods are available to evaluate muscle strength, endurance, and dexterity, there are no validated outcome measures aimed at objectively evaluating q...

Background: Patients with essential tremor have upper limb postural and action tremor often associated with voice tremor. The objective of this study was to objectively examine voice tremor and its response to symptomatic pharmacological treatment in patients with essential tremor using voice analysis consisting of power spectral analysis and mach...

Adductor-type spasmodic dysphonia (ASD) is a task-specific speech disorder characterized by a strangled and strained voice. We have previously demonstrated that advanced voice analysis, performed with support vector machine, can objectively quantify voice impairment in dysphonic patients, also evidencing results of voice improvements due to symptom...

Sign languages (SLs) can aid in improving the communication between hearing impaired and hearing communities, but only a limited number of hearing individuals understand it. SL recognition systems tackle this issue by using sensors to acquire gesture data later converted into spoken or written language by means of machine-learning algorithms. Withi...

A novel bithiophene‐fulleropyrrolidine bisadducts system (bis‐Th2PC60) was synthesized and electropolymerized by chronoamperometry onto flexible ITO/PET substrates. The resulting semitransparent thin film was characterized by XPS, FT‐IR, cyclic voltammetry and optical techniques, confirming the good outcome of the electropolymerization process. AFM...

The voice results in acoustic signals analyzed and synthetized at first for telecommunication matters, and more recently investigated for medical purposes. In particular, voice signal characteristics can evidence individual health conditions useful for screening, diagnostic and remote monitoring aims. Within this frame, the knowledge of baseline fe...

Background: Experimental studies using qualitative or quantitative analysis have demonstrated that the human voice progressively worsens with ageing. These studies, however, have mostly focused on specific voice features without examining their dynamic interaction. To examine the complexity of age-related changes in voice, more advanced techniques...

Currently, the gold-standard method of assessing human motion is by means of optoelectronic analysis systems. However, such systems have some drawbacks (time-consuming procedure, specialized room, expensive, ..) and therefore other analysis systems are gaining in importance. Here, we report a novel inertial-sensor based system (Movit System G1, by...

We propose a sign language recognition system based on wearable electronics and two different classification algorithms. The wearable electronics were made of a sensory glove and inertial measurement units to gather fingers, wrist, and arm/forearm movements. The classifiers were k-Nearest Neighbors with Dynamic Time Warping (that is a non-parametri...

Introduction Adductor-type spasmodic dysphonia is a task-specific focal dystonia characterized by involuntary laryngeal muscle spasms. Due to the lack of quantitative instrumental tools, voice assessment in patients with adductor-type spasmodic dysphonia is mainly based on qualitative neurologic examination. We evaluated patients with cepstral anal...

Background Technology-based objective measures (TOMs) recently gained relevance to support clinicians in the assessment of motor function in Parkinson’s disease (PD), although limited data are available in the early phases. Objective To assess motor performances of a population of newly diagnosed, drug free PD patients using wearable inertial sens...

Correct screening and diagnosis are fundamental for healthcare purposes, to obtain which medical doctors rely on different medical tests to gather knowledges as support to clinical decisions, but which can result with different severities of invasiveness and painfulness. During latest decades, the medical tests seem to trend towards a sensible redu...

Currently, clinical evaluation represents the primary outcome measure in Parkinson's disease (PD). However, clinical evaluation may underscore some subtle motor impairments, hidden from the visual inspection of examiners. Technology-based objective measures are more frequently utilized to assess motor performance and objectively measure motor dysfu...

Advanced prostheses for recovery of arm amputation can be nowadays controlled by the electromyographic (EMG) signals. Implanted myoelectric sensors, suitable to transcutaneous wireless reading, permit to improve the signal-to-noise ratio. This paper explores the feasibility of a through-the-arm telemetry link based on the radiofrequency identificat...

Human maintain their body balance by sensorimotor controls mainly based on information gathered from vision, proprioception and vestibular systems. When there is a lack of information, caused by pathologies, diseases or aging, the subject may fall. In this context, we developed a system to augment information gathering, providing the subject with w...

Due to the fact that no study to date has shown the experimental validity of ACC-based measures of body sway with respect to posturography for subjects with vestibular deficits, the aim of the present study was: i) to develop and validate a practical tool that can allow clinicians to measure postural sway derangements in an otoneurological setting...

In this work, we present a novel multisensory electronic architecture that can work with very low voltage requirements thus enabling power management directly from harvesting-based low-voltage sources. The harvesting system here proposed relays on thermoelectric generator cells useful for furnishing additional power to an electronic system made of...

Tetraplegic people need continuous assistance in every daily activity. Assistive technologies can improve, to a certain degree, their quality of life allowing partial autonomy with powering their residual capability of movements. In this work, we propose a novel wire-free low-cost user-friendly battery-operated sensory headwear, which allows home a...

We here present a 10-17 Degrees of Freedom (DoF) sensory gloves for Smart Healthcare implementing an energy harvesting architecture, aimed at enhancing the battery lasting when powering the electronics of the two different types of gloves, used to sense fingers movements. In particular, we realized a comparison in terms of measurement repeatability...

Objective: The complex nature of Parkinson's disease (PD) makes difficult to rate its severity, mainly based on visual inspection of motor impairments. Wearable sensors have been demonstrated to help overcoming such a difficulty, by providing objective measures of motor abnormalities. However, up to now those sensors have been used on advanced PD...

This book constitutes the thoroughly refereed post-conference proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018, held in Funchal, Madeira, Portugal, in January 2018. The 25 revised full papers presented were carefully reviewed and selected from a total of 299 submissions. The pap...

Developmental coordination disorder (DCD) and attention-deficit hyperactivity disorder (ADHD) are neuro-developmental disorders, starting in childhood, which can affect the planning of movements and the coordination. We investigated how and in which measure a system based on wearable inertial measurement units (IMUs) can provide an objective suppor...

We present a multi-source energy harvesting architecture, aimed to enhancing the battery last in powering the electronics of a sensory glove, capable to sense fingers movements. In particular, the proposed architecture is based on Radio Frequency, Piezoelectric and Thermoelectric harvesters. The glove is equipped with flex sensors and built-in elec...

The median sternotomy can rise in rib and/or sternum micro/macro-fractures and/or brachial plexus injuries, which can even evolve in chronic pain with significant impact on patient’s quality life. Post-sternotomy chronic pain is recognized as a multifactorial complex issue, and it has been assessed that sternum retraction forces, applied by the sur...

Mesoangioblasts are outstanding candidates for stem cell therapy and are already being explored in clinical trials. However, a crucial challenge in regenerative medicine is the limited availability of undifferentiated myogenic progenitor cells, since growth is typically accompanied by differentiation. Here reversible myogenic-differentiation-switch...

Human maintain their body balance by sensorimotor controls mainly based on information gathered from vision, proprioception and vestibular systems. When there is a lack of information, caused by pathologies, diseases or aging, the subject may fall. In this context, we developed a system to augment information gathering, providing the subject with w...

Resistive flex sensors were increasingly used in different areas for their interesting property to change their resistance when bent. In particular, they can be applied to human segment in biomedical devices to register static and dynamic postures. In spite of their interesting properties, such as robustness, low price and long life, they often dem...

Manual dexterity is one of the most important surgical skills, and yet there are limited instruments to evaluate this ability objectively. In this paper, we propose a system designed to track surgeons’ hand movements during simulated open surgery tasks and to evaluate their manual expertise. Eighteen participants, grouped according to their surgica...

In aircraft scenarios the proper interpretation of communication meanings is mandatory for security reasons. In particular some communications, occurring between the signalman and the pilot, rely on arm-and-hand visual signals, which can be prone to misunderstanding in some circumstances as it can be, for instance, because of low-visibility. This w...

Since changes in vestibular function may be one cause of disequilibrium, major advances in measuring postural control and sensory integration in vestibular impairments have been achieved by using posturography. However, in order to overcome problems related to this type of technology, body-worn accelerometers (ACC) have been proposed as a portable,...

This study is aimed at identifying the collateral circulation in case of femoral-aorta-iliac axis obstruction, with the purpose of a more correct therapeutic indication being either medical or surgical or physiotherapeutic or combined.

Support vector machines (SVMs) are widely used classifiers for detecting physiological patterns in human–computer interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are...