Andrea Mannini

• PhD
• Researcher at Fondazione Don Carlo Gnocchi

This work describes an automatic method to recognize the position of an accelerometer worn on five different parts of the body–ankle, thigh, hip, arm and wrist–from raw accelerometer data. Automatic detection of body position of a wearable sensor would enable systems that allow users to wear sensors flexibly on different body parts or permit system...

[PDF AVAILABLE for free till Nov 5th at the following link] http://authors.elsevier.com/a/1PihP4p3hg4Hp0 In this paper we implemented machine learning (ML) and strap-down integration (SDI) methods and analyzed them for their capability of estimating stride-by-stride walking speed. Walking speed was computed by dividing estimated stride length by...

PURPOSE: Large physical activity surveillance projects such as the UK Biobank and NHANES are using wrist-worn accelerometer-based activity monitors that collect raw data. The goal is to increase wear time by asking subjects to wear the monitors on the wrist instead of the hip, and then to use information in the raw signal to improve activity type a...

In this paper we present a classifier based on a hidden Markov model (HMM) that was applied to a gait treadmill dataset for gait phase detection and walking/jogging discrimination. The gait events foot strike, foot flat, heel off, toe off were detected using a uni-axial gyroscope that measured the foot instep angular velocity in the sagittal plane....

The use of on-body wearable sensors is widespread in several academic and industrial domains. Of great interest are their applications in ambulatory monitoring and pervasive computing systems; here, some quantitative analysis of human motion and its automatic classification are the main computational tasks to be pursued. In this paper, we discuss h...

An accurate and reliable functional prognosis is vital to stroke patients addressing rehabilitation, to their families, and healthcare providers. This study aimed at developing and validating externally patient-wise prognostic models of the global functional outcome at discharge from intensive inpatient post-acute rehabilitation after stroke, based...

Background Improving prognostication in patients with a prolonged disorder of consciousness (pDoC) is among the most challenging issues in neurorehabilitation. The aim of this Italian multisite prospective longitudinal study was to identify valuable predictors of the complete recovery of consciousness (emergence from Minimally Conscious State, eMCS...

Good data quality is vital for personalising plans in rehabilitation. Machine learning (ML) improves prognostics but integrating it with Multiple Imputation (MImp) for dealing missingness is an unexplored field. This work aims to provide post-stroke ambulation prognosis, integrating MImp with ML, and identify the prognostic influential factors. Str...

BACKGROUND Diagnostic and prognostic decision-making in patients with Disorders of Consciousness (DoC) is challenging. It has been suggested that spontaneous eye blink rate is an index of patients’ level of consciousness easy to detect in clinical practice. Further blinking features (i.e., amplitude, duration, variability in intervals between blink...

In stroke survivors, persistent seizure activity could be associated with poor functional outcomes. At the same time, antiepileptic over-treatment could hamper post-stroke recovery. We systematically investigated the occurrence of seizures, the prevalence of epileptic discharges, and delta slow waves on electroencephalogram (EEG) and anti-seizure m...

Microelectrode recordings from human peripheral and cranial nerves provide a means to study both afferent and efferent axonal signals at different levels of detail, from multi- to single-unit activity. Their analysis can lead to advancements both in diagnostic and in the understanding of the genesis of neural disorders. However, most of the existin...

Unconsciousness in severe acquired brain injury (sABI) patients occurs with different cognitive and neural profiles. Perturbational approaches, which enable the estimation of proxies for brain reorganization, have added a new avenue for investigating the non‐behavioural diagnosis of consciousness. In this prospective observational study, we conduct...

Objective: There is emerging confidence that quantitative EEG (qEEG) has the potential to inform clinical decision-making and guide individualized rehabilitation after stroke, but consensus on the best EEG biomarkers is needed for translation to clinical practice. This study investigates the spatial qEEG spectral and symmetry distribution in patien...

Objective: Within the continuum of consciousness, patients in a Minimally Conscious State (MCS) may exhibit high-level behavioral responses (MCS+) or may not (MCS-). The evaluation of residual consciousness and related classification is crucial to propose tailored rehabilitation and pharmacological treatments, considering the inherent differences a...

Major Depressive Disorder (MDD) is one of the most common psychological disorders. The multiplicity of its clinical patterns, the varieties of symptoms and the different types of clinical evolution generate many diagnostic difficulties. Currently, MDD assessment is performed through the use of assessment scales and interviews with the patient. This...

Background: The Coma Recovery Scale-Revised (CRS-R) is the most recommended clinical tool to examine the neurobehavioral condition of individuals with disorders of consciousness (DOCs). Different studies have investigated the prognostic value of the information provided by the conventional administration of the scale, while other measures derived...

A domain-specific perspective to cognitive functioning in stroke patients may predict their cognitive recovery over time and target stroke rehabilitation intervention. However, data about domain-specific cognitive impairment after stroke are still scarce. This study prospectively investigated the domain-specific pattern of cognitive impairments, us...

Background: The complexity of stroke sequelae, the heterogeneity of outcome measures and rehabilitation pathways, and the lack of extensively validated prediction models represent a challenge in predicting stroke rehabilitation outcomes. Aim: To prospectively investigate a multidimensional set of variables collected at admission to inpatient pos...

Consciousness can be defined as a phenomenological experience continuously evolving. Current research showed how conscious mental activity can be subdivided into a series of atomic brain states converging to a discrete spatiotemporal pattern of global neuronal firing. Using the high temporal resolution of EEG recordings in patients with a severe Ac...

Injury in sports is an occurrence that prevents athletes from participating in training and competitions and has an incidence of 8.1 injuries/1000 h of practice. This translates into a cost and also into danger, especially if the event is repeated, for the health of the athlete; the injury certainly has a multifactorial causality. On the other hand...

Objective. Brain-injured patients may enter a state of minimal or inconsistent awareness termed minimally conscious state (MCS). Such patient may (MCS+) or may not (MCS-) exhibit high-level behavioral responses, and the two groups retain two inherently different rehabilitative paths and expected outcomes. We hypothesized that brain complexity may b...

Objectives: To verify whether Trunk Control Test (TCT) upon admission to intensive inpatient post-stroke rehabilitation, combined with other confounding variables, is independently associated with discharge mBI. Design: Multicentric retrospective observational cohort study. Setting: Two Italian inpatient rehabilitation units. Participants: P...

Objective: The diagnosis of benign lesions of the vocal fold (BLVF) is still challenging. The analysis of the acoustic signals through the implementation of machine learning models can be a viable solution aimed at offering support for clinical diagnosis. Materials and methods: In this study, a support vector machine was trained and cross-valida...

Detecting signs of residual neural activity in patients with altered states of consciousness is a crucial issue for the customization of neurorehabilitation treatments and clinical decision-making. With this large observational prospective study, we propose an innovative approach to detect residual signs of consciousness via the assessment of the a...

The use of stereophotogrammetry systems is challenging when targeting children’s gait analysis due to the time required and the need to keep physical markers in place. For this reason, marker-less photoelectric systems appear to be a solution for accurate and fast gait analysis in youth. The aim of this study is to validate a photoelectric system a...

Poor dynamic balance and impaired gait adaptation to different contexts are hallmarks of people with neurological disorders (PwND), leading to difficulties in daily life and increased fall risk. Frequent assessment of dynamic balance and gait adaptability is therefore essential for monitoring the evolution of these impairments and/or the long-term...

Objectives The “cognitive reserve” (CR) theory posits that higher premorbid cognitive activities can mitigate the effects of brain damage. This study aimed to investigate the association between CR and long-term functional autonomy in patients surviving a severe traumatic brain injury (sTBI). Setting Data were collected from the database of inpati...

The inflammatory, reparative and regenerative mechanisms activated in ischemic stroke patients immediately after the event cooperate in the response to injury, in the restoration of functions and in brain remodeling even weeks after the event and can be sustained by the rehabilitation treatment. Nonetheless, patients’ response to treatments is diff...

The prognosis of neurological outcomes in patients with prolonged Disorders of Consciousness (pDoC) has improved in the last decades. Currently, the level of consciousness at admission to post-acute rehabilitation is diagnosed by the Coma Recovery Scale-Revised (CRS-R) and this assessment is also part of the used prognostic markers. The consciousne...

Objective Clinical responsiveness of patients with a Disorder of Consciousness (DoC) correlates to sympathetic/parasympathetic homeostatic balance. Heart Rate Variability (HRV) metrics result in non-invasive proxies of modulation capabilities of visceral states. In this work, our aim was to evaluate whether HRV measures could improve the differenti...

Decoding human motor intentions by processing electrophysiological signals is a crucial, yet unsolved, challenge for the development of effective upper limb prostheses. Pattern recognition of continuous myoelectric (EMG) signals represents the state-of-art for multi-DoF prosthesis control. However, this approach relies on the unreliable assumption...

Background: Stroke survivors report physical, cognitive, and psychological impairments, with a consequent limitation of participation. Participation is the most context-related dimension of functioning, but the literature on participation in Italian stroke patients is scant. Aim: This study aimed to describe the recovery of participation six mon...

Background: Autonomic Nervous System (ANS) activity, as cardiac, respiratory and electrodermal activity, has been shown to provide specific information on different consciousness states. Respiration rates (RRs) are considered indicators of ANS activity and breathing patterns are currently already included in the evaluation of patients in critical c...

Dysphagia represents one of the most frequent symptoms in the post–acute stroke population. Swallowing impairment and cognitive deficits can often co-occur. This study aims to investigate the relationship between cognitive impairment and the recovery of dysphagia in patients attending specific rehabilitation. Patients admitted to intensive rehabili...

Lateral brain symmetry indexes, detected by electroencephalography (EEG), are markers of rehabilitative recovery widely used in patients with severe acquired brain injury (sABI). In this study, Machine Learning algorithms were cross-validated to detect consistent asymmetries, starting from a completely automated features extraction pipeline in the...

Recent studies on human upper limb motion highlighted the benefit of dimensionality reduction techniques to extrapolate informative joint patterns. These techniques can simplify the description of upper limb kinematics in physiological conditions, serving as a baseline for the objective assessment of movement alterations, or to be implemented in a...

Prognosis of prolonged Disorders of Consciousness (pDoC) is influenced by patients' clinical diagnosis and Coma Recovery Scale-Revised (CRS-R) total score. We compared the prognostic accuracy of a novel Consciousness Domain Index (CDI) with that of clinical diagnosis and CRS-R total score, for recovery of full consciousness at 6-, 12-, and 24-month...

Background: The Token Test (TT) is widely used to examine comprehension disorders in aphasic patients, but abilities other than language may affect a patient’s performance. This study aims to explore the correlation between the TT subtest performances and the performances in extra-linguistic cognitive areas in a cohort of patients from the Intensiv...

Objective Disorders of consciousness (DoC) are acquired conditions of severely altered consciousness. Electroencephalography (EEG)-derived biomarkers have been studied as clinical predictors of consciousness recovery. Therefore, this study aimed to systematically review the methods, features, and models used to derive prognostic EEG markers in pati...

Background: Sporadic CAA is recognized as a major cause of sICH and sABI. Even if intensive rehabilitation is recommended to maximize functional recovery after sICH, no data are available on whether CAA may affect rehabilitation outcomes. In this observational prospective study, to explore the impact of CAA on rehabilitation results, functional out...

Introduction: The heterogeneity of procedures and the variety of comorbidities of the patients undergoing surgery in an emergency setting makes perioperative risk stratification, planning, and risk mitigation crucial. In this optic, Machine Learning has the capability of deriving data-driven predictions based on multivariate interactions of thousan...

Background Stroke represents the second preventable cause of death after cardiovascular disease and the third global cause of disability. In countries where national registries of the clinical quality of stroke care have been established, the publication and sharing of the collected data have led to an improvement in the quality of care and surviva...

Introduction Major Depressive Disorder (MDD) causes a variety of emotional and physical issues leading to severe clinical implications [1]. In MDD patients, a strong association between psychomotor deterioration and gait components has been found [2]. Instrumental gait analysis holds a crucial role in precision evaluation of movement in MDD [3]. Ta...

Background: A proportion of patients with COVID-19 need hospitalization due to severe respiratory symptoms. We sought to analyze characteristics of survivors of severe COVID-19 subsequently admitted to in-patient pulmonary rehabilitation and identify their rehabilitation needs. Methods: From the COVID-19 Registry of Fondazione Don Gnocchi, we ex...

Background Rehabilitation treatments and services are essential for the recovery of post-stroke patients’ functions; however, the increasing number of available therapies and the lack of consensus among outcome measures compromises the possibility to determine an appropriate level of evidence. Machine learning techniques for prognostic applications...

Patients with severe acquired brain injury and prolonged disorders of consciousness (pDoC) are characterized by high clinical complexity and high risk to develop medical complications. The present multi-center longitudinal study aimed at investigating the impact of medical complications on the prediction of clinical outcome by means of machine lear...

The state of the art is still lacking an extensive analysis of which clinical characteristics are leading to better outcomes after robot-assisted rehabilitation on post-stroke patients. Prognostic machine learning-based models could promote the identification of predictive factors and be exploited as Clinical Decision Support Systems (CDSS). For th...

Assessing consciousness results in one of the most complex neurological diagnosis. Even more complex and uncertain is prognosticating on consciousness recovery. Currently, consciousness is assessed by using a six-items scale, the Coma Recovery Scale-Revised. Namely, scores on the sub-items can individually assign or not a specific level of consciou...

Targeted muscle reinnervation (TMR) is a surgical procedure which allows to restore myoelectric control sources in people with proximal upper-limb amputations. However, the large physical displacement generally provoked by the reinnervated muscles following contraction can represent a drawback for the use of surface electrodes, which are affected b...

Background Stroke related motor function deficits affect patients' likelihood of returning to professional activities, limit their participation in society and functionality in daily living. Hence, robot-aided gait rehabilitation needs to be fruitful and effective from a motor learning perspective. For this reason, optimal human–robot interaction s...

Background Rehabilitation medicine is facing a new development phase thanks to a recent wave of rigorous clinical trials aimed at improving the scientific evidence of protocols. This phenomenon, combined with new trends in personalised medical therapies, is expected to change clinical practice dramatically. The emerging field of Rehabilomics is onl...

Patients with Disorder of Consciousness (DoC) entering Intensive Rehabilitation Units after a severe Acquired Brain Injury have a highly variable evolution of the state of consciousness which is a complex aspect to predict. Besides clinical factors, electroencephalography has clearly shown its potential into the identification of prognostic biomark...

Archery is a sport accessible to a wide range of people, no matter their age, gender or ability, and can be practiced both by able-bodied and impaired athletes on a level playing field. The recent increase in the number of studies concerning the biomechanical evaluation of the archery discipline revealed the need to advance an evidence-based approa...

Background Due to continuous advances in intensive care technology and neurosurgical procedures, the number of survivors from severe acquired brain injuries (sABIs) has increased considerably, raising several delicate ethical issues. The heterogeneity and complex nature of the neurological damage of sABIs make the detection of predictive factors of...

Background: Disorders of consciousness (DoCs) include unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS). Critical illness polyneuropathy and myopathy (CIPNM) is frequent in severe acquired brain injuries and impacts functional outcomes at discharge from the intensive rehabilitation unit (IRU). We investigated the prevalenc...

Background Trunk control plays a crucial role in the stroke rehabilitation, but it is unclear which factors could influence the trunk control after an intensive rehabilitation treatment. Objectives To study which demographic, clinical and functional variables could predict the recovery of trunk control after intensive post-stroke inpatient rehabil...

COVID-19 cases are increasing around the globe with almost 5 million of deaths. We propose here a deep learning model capable of predicting the duration of the infection by means of information available at hospital admission. A total of 222 patients were enrolled in our observational study. Anagraphical and anamnestic data, COVID-19 signs and symp...

Human motion analysis is a field of increasing interest. In most applications, an accurate estimation of joint angles is needed. Inertial Measurement Units (MIMUs) represent a very promising technology for motion capture. Unfortunately, their performances are strongly influenced by several sources of error (e.g., gyroscopes biases). To limit the ef...

This study proposes the instrumental analysis of the physiological and biomechanical adaptation of football players to a fatigue protocol during the month immediately after the COVID-19 lockdown, to get insights into fitness recovery. Eight male semi-professional football players took part in the study and filled a questionnaire about their activit...

Purpose Decompressive craniectomy (DC) is a life-saving procedure conducted to treat refractory intracranial hypertension. Although DC reduces mortality of severe Acquired Brain Injury (sABI) survivors, it has been associated with severe long-term disability. This observational study compares functional outcomes at discharge from an Intensive Rehab...

Objectives This study aims to evaluate the diagnostic performance of NIHSS extinction and inattention item, compared to the results of the Oxford Cognitive Screen (OCS) heart subtest. Additionally, the possible role of the NIHSS visual field subtest on the NIHSS extinction and inattention subtest performance is explored and discussed. Methods We a...

PurposeCOVID-19 pandemic has affected most components of health systems including rehabilitation. The study aims to compare demographic and clinical data of patients admitted to an intensive rehabilitation unit (IRU) after severe acquired brain injuries (sABIs), before and during the pandemic.Materials and methodsIn this observational retrospective...

Objective: The aim of this study was to describe an innovative methodology of a registry development, constantly updated for the scientific assessment and analysis of the health status of the population with COVID-19. Study design and setting: A methodological study design to develop a multi-site, Living COVID-19 Registry of COVID-19 patients ad...

Archery technique requires a coordinated activation of shoulder girdle and upper extremity muscles to perform a successful shot. The analysis of muscle synergies can provide information about the motor strategy that underlies the shooting performance, also supporting the investigation of motor impairments in athletes with disability. For this purpo...

Human motion analysis is gaining increased importance in several fields, from movement assessment in rehabilitation to recreational applications such as virtual coaching. Among all the technologies involved in motion capture, Magneto-Inertial Measurements Units (MIMUs) is one of the most promising due to their small dimensions and low costs. Nevert...

The aim of this study is to propose and validate an inertial sensors-based methodology for the para-rowing stroke cycles segmentation. One non-disabled athlete performed two para-rowing setups , simulating PR1 (arms and shoulders-AS) and PR2 (trunk and arms-TA) conditions. Catch and finish events of each stroke cycle were identified on the signals...

Background and objectives From a rehabilitation perspective, removal of tracheostomy in patients with severe acquired brain injuries (sABI) is a crucial step. Predictive parameters for a successful decannulation are currently still a focus of the research for sABI patients, especially for those presenting a disorder of consciousness. For this reaso...

Background and Objectives Magnetic tracking involves the use of magnetic sensors to localize one or more magnetic objectives, in those applications in which a free line-of-sight between them and the operator is hampered. We applied this concept to prosthetic hands, which could be controlled by tracking permanent magnets implanted in the forearm mus...

Magnetic Inertial Measurement Units (MIMUs) represent an increasingly used technology in the field of human motion. However, their applications are strongly affected by magnetic disturbances and poor calibration, which could determine inaccurate attitude estimations. Thus, Inertial Measurement Units (IMUs), relying exclusively on accelerometers and...

This work assesses the feasibility of wearable magneto-inertial measurement units (MIMUs) for the segmentation of the archery shooting technique in athletes with and without disability. MIMU-based segmentation was validated against stereophotogrammetry, showing good reliability.

We propose a machine learning model capable of predicting COVID-19 post-acute rehabilitation duration by means of data taken before the start of the rehabilitative path. Data from 62 patients recovering after SARS-CoV2 infection were processed in our study. Anagraphical and anamnestic data, COVID-19 signs and symptoms, COVID-19-related therapy, hae...

Background: The aim of the study was to describe the epidemiological characteristics of Nursing Homes (NHs) residents infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and to compute the related case-fatality rate. Materials and methods: The outcomes were mortality and case-fatality rate with related epidemiologi...

Objectives This study aims to evaluate the diagnostic performance of NIHSS extinction and inattention item, compared to the results of the Oxford Cognitive Screen (OCS) heart subtest. Additionally, the possible role of the NIHSS visual field subtest on the NIHSS extinction and inattention subtest performance is explored and discussed. Methods We a...

Background: The complex nature of stroke sequelae, the heterogeneity in rehabilitation pathways, and the lack of validated prediction models of rehabilitation outcomes challenge stroke rehabilitation quality assessment and clinical research. An integrated care pathway (ICP), defining a reproducible rehabilitation assessment and process, may provide...

The interest and competitiveness in sports for persons with disabilities has increased significantly in the recent years, creating a demand for technological tools supporting practice. Wearable sensors offer non-invasive, portable and overall convenient ways to monitor sports practice. This systematic review aims at providing current evidence on th...

Quantifying muscle fatigue is a key aspect of everyday sport practice. A reliable and objective solution that can fulfil this task would be deeply important for two main reasons: (i) it would grant an objective indicator to adjust the daily training load for each player and (ii) it would provide an innovative tool to reduce the risk of fatigue-rela...

Myoelectric upper limb prostheses are controlled using information from the electrical activity of residual muscles (i.e. the electromyogram, EMG). EMG patterns at the onset of a contraction (transient phase) have shown predictive information about upcoming grasps. However, decoding this information for the estimation of the grasp force was so far...

Objectives Critical illness polyneuropathy and myopathy (CIPNM) frequently affects critical patients and can occur after severe acquired brain injuries (sABI) influencing the functional recovery. We aimed to assess how the concomitance between CIPNM and sABI might influence the rehabilitative outcomes in terms of functional autonomy, oral feeding r...

Although inertial and magnetic wearable sensors are promising tools to develop novel technologies for human motion capture, their diffusion is being limited by their fair accuracy. In indoor applications, most of the inaccuracy comes from the magnetic disturbances contained in the magnetometer data. Besides, non-technicians might easily fail in pro...