Distribution of arm velocity and frequency of arm usage during daily activity: objective outcome evaluation after shoulder surgery.

In clinical settings, functional evaluation of shoulder movement is primarily based on what the patient thinks he/she is able to do rather than what he/she is actually performing. We proposed a new approach for shoulder assessment based on inertial sensors to monitor arm movement in the daily routine. The detection of movement of the humerus relative to the trunk was first validated in a laboratory setting (sensitivity>95%, specificity>97%). Then, 41 control subjects and 21 patients suffering from a rotator cuff tear were evaluated (before and after surgery) using clinical questionnaires and a one-day measurement of arm movement. The quantity of movement was estimated with the movement frequency and its symmetry index (SIFr). The quality of movement was assessed using the Kolmogorov-Smirnov distance (KS) between the cumulative distribution of the arm velocity for controls and the same distribution for each patient. SIFr presented differences between patients and controls at 3 month follow-up (p<0.05) while KS showed differences also after 6 months (p<0.01). SIFr illustrated a change in dominance due to the disorder whereas KS, which appeared independent of the dominance and occupation, showed a change in movement velocity. Both parameters were correlated to clinical scores (R(2) reaching 0.5). This approach provides clinicians with new objective parameters for evaluating the functional ability of the shoulder in daily conditions, which could be useful for outcome assessment after surgery.

Estimating dominant upper-limb segments during daily activity.

A new method of evaluation for functional assessment of the shoulder during daily activity is presented. An ambulatory system using inertial sensors attached on the humerus was used to differentiate a dominant from a non-dominant shoulder. The method was tested on 31 healthy volunteers with no shoulder pathology while carrying the system during 8h of their daily life. Shoulder mobility based on the angular velocities and the accelerations of the humerus were calculated and compared every 5s for both sides. Our data showed that the dominant arm of the able bodied participants was more active than the non-dominant arm for standing (+20% for the right handed, +15% for the left handed) and sitting (+24% for the right handed, +32% for the left handed) posture, while for the walking periods the use of the right and left side was almost identical. The proposed method could be used to objectively quantify upper-limb usage during activities of daily living in various shoulder disorders.

Outcome of unilateral ankle arthrodesis and total ankle replacement in terms of bilateral gait mechanics.

Previous studies assessed the outcome of ankle arthrodesis (AA) and total ankle replacement (TAR) surgeries; however, the extent of postoperative recovery towards bilateral gait mechanics (BGM) is unknown. We evaluated the outcome of the two surgeries at least 2 years post rehabilitation, focusing on BGM. 36 participants, including 12 AA patients, 12 TAR patients, and 12 controls were included. Gait assessment over 50 m distance was performed utilizing pressure insoles and 3D inertial sensors, following which an intraindividual comparison was performed. Most spatiotemporal and kinematic parameters in the TAR group were indicative of good gait symmetry, while the AA group presented significant differences. Plantar pressure symmetry among the AA group was also significantly distorted. Abnormality in biomechanical behavior of the AA unoperated, contralateral foot was observed. In summary, our results indicate an altered BGM in AA patients, whereas a relatively fully recovered BGM is observed in TAR patients, despite the quantitative differences in several parameters when compared to a healthy population. Our study supports a biomechanical assessment and rehabilitation of both operated and unoperated sides after major surgeries for ankle osteoarthrosis.

Characterization of gait in female patients with moderate to severe hallux valgus deformity.

BACKGROUND: Hallux valgus is one of the most common forefoot problems in females. Studies have looked at gait alterations due to hallux valgus deformity, assessing temporal, kinematic or plantar pressure parameters individually. The present study, however, aims to assess all listed parameters at once and to isolate the most clinically relevant gait parameters for moderate to severe hallux valgus deformity with the intent of improving post-operative patient prognosis and rehabilitation. METHODS: The study included 26 feet with moderate to severe hallux valgus deformity and 30 feet with no sign of hallux valgus in female participants. Initially, weight bearing radiographs and foot and ankle clinical scores were assessed. Gait assessment was then performed utilizing pressure insoles (PEDAR®) and inertial sensors (Physilog®) and the two groups were compared using a non-parametric statistical hypothesis test (Wilcoxon rank sum, P<0.05). Furthermore, forward stepwise regression was used to reduce the number of gait parameters to the most clinically relevant and correlation of these parameters was assessed with the clinical score. FINDINGS: Overall, the results showed clear deterioration in several gait parameters in the hallux valgus group compared to controls and 9 gait parameters (effect size between 1.03 and 1.76) were successfully isolated to best describe the altered gait in hallux valgus deformity (r(2)=0.71) as well as showed good correlation with clinical scores. INTERPRETATION: Our results, and nine listed parameters, could serve as benchmark for characterization of hallux valgus and objective evaluation of treatment efficacy.

Energetics and mechanics of walking in patients with chronic low back pain and healthy matched controls.

PURPOSE: Walking in patients with chronic low back pain (cLBP) is characterized by motor control adaptations as a protective strategy against further injury or pain. The purpose of this study was to compare the preferred walking speed, the biomechanical and the energetic parameters of walking at different speeds between patients with cLBP and healthy men individually matched for age, body mass and height. METHODS: Energy cost of walking was assessed with a breath-by-breath gas analyser; mechanical and spatiotemporal parameters of walking were computed using two inertial sensors equipped with a triaxial accelerometer and gyroscope and compared in 13 men with cLBP and 13 control men (CTR) during treadmill walking at standard (0.83, 1.11, 1.38, 1.67 m s(-1)) and preferred (PWS) speeds. Low back pain intensity (visual analogue scale, cLBP only) and perceived exertion (Borg scale) were assessed at each walking speed. RESULTS: PWS was slower in cLBP [1.17 (SD = 0.13) m s(-1)] than in CTR group [1.33 (SD = 0.11) m s(-1); P = 0.002]. No significant difference was observed between groups in mechanical work (P ≥ 0.44), spatiotemporal parameters (P ≥ 0.16) and energy cost of walking (P ≥ 0.36). At the end of the treadmill protocol, perceived exertion was significantly higher in cLBP [11.7 (SD = 2.4)] than in CTR group [9.9 (SD = 1.1); P = 0.01]. Pain intensity did not significantly increase over time (P = 0.21). CONCLUSIONS: These results do not support the hypothesis of a less efficient walking pattern in patients with cLBP and imply that high walking speeds are well tolerated by patients with moderately disabling cLBP.

A Test Bed Applied Mobile Robot Navigation

It is presented a test bed applied to studies on dynamics, control, and navigation of mobile robots. A cargo ship scale model was chosen, which can be radio-controlled or operated autonomously through an embedded control system. A control program, which manages on board mission execution, is implemented on a microcontroller. Navigation is based on an electronic compass, which includes automatic compensation for pitch and roll motions. Heading control loop is based on this sensor, and on a rudder positioning system. A propulsion control system is also implemented. Typical manoeuvres as the turning test and "zig-zag", were implemented and tested. They are included on a manoeuvre library, and can be accessed independently or in combined modes. The embedded system is also in charge of signal acquisition and storing during the missions. It is possible to analyse experiments on identification of ship dynamics, control, and navigation, through the data transferred to a PC by serial communication. Navigation is going to be improved by including inertial sensors on board, and a DGPS. Preliminary tests are aimed to ship identification, and manoeuvrability, using free model tests. Future steps include extending this system for developing other mobile robots as, ROVs, AUVs, and aerial vehicles.

Single-mode acceleration of matter waves in circular waveguides

Ultracold gases in ring geometries hold promise for significant improvements of gyroscopic sensitivity. Recent experiments have realized atomic and molecular storage rings with radii in the centimeter range, sizes whose practical use in inertial sensors requires velocities significantly in excess of typical recoil velocities. We use a combination of analytical and numerical techniques to study the coherent acceleration of matter waves in circular waveguides, with particular emphasis on its impact on single-mode propagation. In the simplest case we find that single-mode propagation is best maintained by the application of time-dependent acceleration force with the temporal profile of a Blackmann pulse. We also assess the impact of classical noise on the acceleration process.

Influência da injunção da base na fototriangulação de imagens obtidas com uma unidade de mapeamento móvel

Pós-graduação em Ciências Cartográficas - FCT

Rehabilitation Engineering in Parkinson's disease

Impairment of postural control is a common consequence of Parkinson's disease (PD) that becomes more and more critical with the progression of the disease, in spite of the available medications. Postural instability is one of the most disabling features of PD and induces difficulties with postural transitions, initiation of movements, gait disorders, inability to live independently at home, and is the major cause of falls. Falls are frequent (with over 38% falling each year) and may induce adverse consequences like soft tissue injuries, hip fractures, and immobility due to fear of falling. As the disease progresses, both postural instability and fear of falling worsen, which leads patients with PD to become increasingly immobilized. The main aims of this dissertation are to: 1) detect and assess, in a quantitative way, impairments of postural control in PD subjects, investigate the central mechanisms that control such motor performance, and how these mechanism are affected by levodopa; 2) develop and validate a protocol, using wearable inertial sensors, to measure postural sway and postural transitions prior to step initiation; 3) find quantitative measures sensitive to impairments of postural control in early stages of PD and quantitative biomarkers of disease progression; and 4) test the feasibility and effects of a recently-developed audio-biofeedback system in maintaining balance in subjects with PD. In the first set of studies, we showed how PD reduces functional limits of stability as well as the magnitude and velocity of postural preparation during voluntary, forward and backward leaning while standing. Levodopa improves the limits of stability but not the postural strategies used to achieve the leaning. Further, we found a strong relationship between backward voluntary limits of stability and size of automatic postural response to backward perturbations in control subjects and in PD subjects ON medication. Such relation might suggest that the central nervous system presets postural response parameters based on perceived maximum limits and this presetting is absent in PD patients OFF medication but restored with levodopa replacement. Furthermore, we investigated how the size of preparatory postural adjustments (APAs) prior to step initiation depend on initial stance width. We found that patients with PD did not scale up the size of their APA with stance width as much as control subjects so they had much more difficulty initiating a step from a wide stance than from a narrow stance. This results supports the hypothesis that subjects with PD maintain a narrow stance as a compensation for their inability to sufficiently increase the size of their lateral APA to allow speedy step initiation in wide stance. In the second set of studies, we demonstrated that it is possible to use wearable accelerometers to quantify postural performance during quiet stance and step initiation balance tasks in healthy subjects. We used a model to predict center of pressure displacements associated with accelerations at the upper and lower back and thigh. This approach allows the measurement of balance control without the use of a force platform outside the laboratory environment. We used wearable accelerometers on a population of early, untreated PD patients, and found that postural control in stance and postural preparation prior to a step are impaired early in the disease when the typical balance and gait intiation symptoms are not yet clearly manifested. These novel results suggest that technological measures of postural control can be more sensitive than clinical measures. Furthermore, we assessed spontaneous sway and step initiation longitudinally across 1 year in patients with early, untreated PD. We found that changes in trunk sway, and especially movement smoothness, measured as Jerk, could be used as an objective measure of PD and its progression. In the third set of studies, we studied the feasibility of adapting an existing audio-biofeedback device to improve balance control in patients with PD. Preliminary results showed that PD subjects found the system easy-to-use and helpful, and they were able to correctly follow the audio information when available. Audiobiofeedback improved the properties of trunk sway during quiet stance. Our results have many implications for i) the understanding the central mechanisms that control postural motor performance, and how these mechanisms are affected by levodopa; ii) the design of innovative protocols for measuring and remote monitoring of motor performance in the elderly or subjects with PD; and iii) the development of technologies for improving balance, mobility, and consequently quality of life in patients with balance disorders, such as PD patients with augmented biofeedback paradigms.

Riabilitazione e valutazione di pazienti con deficit neurologici mediante l'utilizzo di realtà virtuale, feedback aumentati, sensori inerziali e tecnologie video a basso costo.

La neuroriabilitazione è un processo attraverso cui individui affetti da patologie neurologiche mirano al conseguimento di un recupero completo o alla realizzazione del loro potenziale ottimale benessere fisico, mentale e sociale. Elementi essenziali per una riabilitazione efficace sono: una valutazione clinica da parte di un team multidisciplinare, un programma riabilitativo mirato e la valutazione dei risultati conseguiti mediante misure scientifiche e clinicamente appropriate. Obiettivo principale di questa tesi è stato sviluppare metodi e strumenti quantitativi per il trattamento e la valutazione motoria di pazienti neurologici. I trattamenti riabilitativi convenzionali richiedono a pazienti neurologici l’esecuzione di esercizi ripetitivi, diminuendo la loro motivazione. La realtà virtuale e i feedback sono in grado di coinvolgerli nel trattamento, permettendo ripetibilità e standardizzazione dei protocolli. È stato sviluppato e valutato uno strumento basato su feedback aumentati per il controllo del tronco. Inoltre, la realtà virtuale permette l’individualizzare il trattamento in base alle esigenze del paziente. Un’applicazione virtuale per la riabilitazione del cammino è stata sviluppata e testata durante un training su pazienti di sclerosi multipla, valutandone fattibilità e accettazione e dimostrando l'efficacia del trattamento. La valutazione quantitativa delle capacità motorie dei pazienti viene effettuata utilizzando sistemi di motion capture. Essendo il loro uso nella pratica clinica limitato, una metodologia per valutare l’oscillazione delle braccia in soggetti parkinsoniani basata su sensori inerziali è stata proposta. Questi sono piccoli, accurati e flessibili ma accumulano errori durante lunghe misurazioni. È stato affrontato questo problema e i risultati suggeriscono che, se il sensore è sul piede e le accelerazioni sono integrate iniziando dalla fase di mid stance, l’errore e le sue conseguenze nella determinazione dei parametri spaziali sono contenuti. Infine, è stata presentata una validazione del Kinect per il tracking del cammino in ambiente virtuale. Risultati preliminari consentono di definire il campo di utilizzo del sensore in riabilitazione.

Biomedical engineering for healthy ageing. Predictive tools for falls

Falls are common and burdensome accidents among the elderly. About one third of the population aged 65 years or more experience at least one fall each year. Fall risk assessment is believed to be beneficial for fall prevention. This thesis is about prognostic tools for falls for community-dwelling older adults. We provide an overview of the state of the art. We then take different approaches: we propose a theoretical probabilistic model to investigate some properties of prognostic tools for falls; we present a tool whose parameters were derived from data of the literature; we train and test a data-driven prognostic tool. Finally, we present some preliminary results on prediction of falls through features extracted from wearable inertial sensors. Heterogeneity in validation results are expected from theoretical considerations and are observed from empirical data. Differences in studies design hinder comparability and collaborative research. According to the multifactorial etiology of falls, assessment on multiple risk factors is needed in order to achieve good predictive accuracy.

Sensor-based evaluation of Circadian motor behavior in people with Dementia. Development and validation of analysis strategies

[ITA]La demenza consiste nel deterioramento, spesso progressivo, dello stato cognitivo di un individuo. Chi è affetto da demenza, presenta alterazioni a livello cognitivo, comportamentale e motorio, ad esempio compiendo gesti ossessivi, ripetitivi, senza uno scopo preciso. La condizione dei pazienti affetti da demenza è valutata clinicamente tramite apposite scale e le informazioni relative al comportamento vengono raccolte intervistando chi se ne occupa, come familiari, il personale infermieristico o il medico curante. Spesso queste valutazioni si rivelano inaccurate, possono essere fortemente influenzate da considerazioni soggettive, e sono dispendiose in termini di tempo. Si ha quindi l'esigenza di disporre di metodiche oggettive per valutare il comportamento motorio dei pazienti e le sue alterazioni patologiche; i sensori inerziali indossabili potrebbero costituire una valida soluzione, per questo scopo. L'obiettivo principale della presente attività di tesi è stato definire e implementare un software per una valutazione oggettiva, basata su sensori, del pattern motorio circadiano, in pazienti affetti da demenza ricoverati in un'unità di terapia a lungo termine, che potrebbe evidenziare differenze nei sintomi della malattia che interessano il comportamento motorio, come descritto in ambito clinico. Lo scopo secondario è stato quello di verificare i cambiamenti motori pre- e post-intervento in un sottogruppo di pazienti, a seguito della somministrazione di un programma sperimentale di intervento basato su esercizi fisici. --------------- [ENG]Dementia involves deterioration, often progressive, of a person's cognitive status. Those who suffer from dementia, present alterations in cognitive and motor behavior, for example performing obsessive and repetitive gestures, without a purpose. The condition of patients suffering from dementia is clinically assessed by means of specific scales and information relating to the behavior are collected by interviewing caregivers, such as the family, nurses, or the doctor. Often it turns out that these are inaccurate assessments that may be heavily influenced by subjective evaluations and are costly in terms of time. Therefore, there is the need for objective methods to assess the patients' motor behavior and the pathological changes; wearable inertial sensors may represent a viable option, so this aim. The main objective of this thesis project was to define and implement a software for a sensor-based assessment of the circadian motor pattern in patients suffering from dementia, hospitalized in a long-term care unit, which could highlight differences in the disease symptoms affecting the motor behavior, as described in the clinical setting. The secondary objective was to verify pre- and post-intervention changes in the motor patterns of a subgroup of patients, following the administration of an experimental program of intervention based on physical exercises.

Fine-grained indoor positioning and tracking systems

Indoor positioning has attracted considerable attention for decades due to the increasing demands for location based services. In the past years, although numerous methods have been proposed for indoor positioning, it is still challenging to find a convincing solution that combines high positioning accuracy and ease of deployment. Radio-based indoor positioning has emerged as a dominant method due to its ubiquitousness, especially for WiFi. RSSI (Received Signal Strength Indicator) has been investigated in the area of indoor positioning for decades. However, it is prone to multipath propagation and hence fingerprinting has become the most commonly used method for indoor positioning using RSSI. The drawback of fingerprinting is that it requires intensive labour efforts to calibrate the radio map prior to experiments, which makes the deployment of the positioning system very time consuming. Using time information as another way for radio-based indoor positioning is challenged by time synchronization among anchor nodes and timestamp accuracy. Besides radio-based positioning methods, intensive research has been conducted to make use of inertial sensors for indoor tracking due to the fast developments of smartphones. However, these methods are normally prone to accumulative errors and might not be available for some applications, such as passive positioning. This thesis focuses on network-based indoor positioning and tracking systems, mainly for passive positioning, which does not require the participation of targets in the positioning process. To achieve high positioning accuracy, we work on some information of radio signals from physical-layer processing, such as timestamps and channel information. The contributions in this thesis can be divided into two parts: time-based positioning and channel information based positioning. First, for time-based indoor positioning (especially for narrow-band signals), we address challenges for compensating synchronization offsets among anchor nodes, designing timestamps with high resolution, and developing accurate positioning methods. Second, we work on range-based positioning methods with channel information to passively locate and track WiFi targets. Targeting less efforts for deployment, we work on range-based methods, which require much less calibration efforts than fingerprinting. By designing some novel enhanced methods for both ranging and positioning (including trilateration for stationary targets and particle filter for mobile targets), we are able to locate WiFi targets with high accuracy solely relying on radio signals and our proposed enhanced particle filter significantly outperforms the other commonly used range-based positioning algorithms, e.g., a traditional particle filter, extended Kalman filter and trilateration algorithms. In addition to using radio signals for passive positioning, we propose a second enhanced particle filter for active positioning to fuse inertial sensor and channel information to track indoor targets, which achieves higher tracking accuracy than tracking methods solely relying on either radio signals or inertial sensors.

A multimodal tablet-based interface for designing and reviewing 3D engineering models

The ability to view and interact with 3D models has been happening for a long time. However, vision-based 3D modeling has only seen limited success in applications, as it faces many technical challenges. Hand-held mobile devices have changed the way we interact with virtual reality environments. Their high mobility and technical features, such as inertial sensors, cameras and fast processors, are especially attractive for advancing the state of the art in virtual reality systems. Also, their ubiquity and fast Internet connection open a path to distributed and collaborative development. However, such path has not been fully explored in many domains. VR systems for real world engineering contexts are still difficult to use, especially when geographically dispersed engineering teams need to collaboratively visualize and review 3D CAD models. Another challenge is the ability to rendering these environments at the required interactive rates and with high fidelity. In this document it is presented a virtual reality system mobile for visualization, navigation and reviewing large scale 3D CAD models, held under the CEDAR (Collaborative Engineering Design and Review) project. It’s focused on interaction using different navigation modes. The system uses the mobile device's inertial sensors and camera to allow users to navigate through large scale models. IT professionals, architects, civil engineers and oil industry experts were involved in a qualitative assessment of the CEDAR system, in the form of direct user interaction with the prototypes and audio-recorded interviews about the prototypes. The lessons learned are valuable and are presented on this document. Subsequently it was prepared a quantitative study on the different navigation modes to analyze the best mode to use it in a given situation.

User-independent accelerometer-based gesture recognition for mobile devices

Many mobile devices embed nowadays inertial sensors. This enables new forms of human-computer interaction through the use of gestures (movements performed with the mobile device) as a way of communication. This paper presents an accelerometer-based gesture recognition system for mobile devices which is able to recognize a collection of 10 different hand gestures. The system was conceived to be light and to operate in a user -independent manner in real time. The recognition system was implemented in a smart phone and evaluated through a collection of user tests, which showed a recognition accuracy similar to other state-of-the art techniques and a lower computational complexity. The system was also used to build a human -robot interface that enables controlling a wheeled robot with the gestures made with the mobile phone.