Chiara Mancinelli

Impact of Tai Chi exercise on multiple fracture-related risk factors in post-menopausal osteopenic women: a pilot pragmatic, randomized trial

BackgroundTai Chi (TC) is a mind-body exercise that shows potential as an effective and safe intervention for preventing fall-related fractures in the elderly. Few randomized trials have simultaneously evaluated TCs potential to reduce bone loss and improve fall-predictive balance parameters in osteopenic women.MethodsIn a pragmatic randomized trial, 86 post-menopausal osteopenic women, aged 45-70, were recruited from community clinics. Women were assigned to either nine months of TC training plus usual care (UC) vs. UC alone. Primary outcomes were changes between baseline and nine months of bone mineral density (BMD) of the proximal femur and lumbar spine (dual-energy X-ray absorptiometry) and serum markers of bone resorption and formation. Secondary outcomes included quality of life. In a subsample (n = 16), quiet standing fall-predictive sway parameters and clinical balance tests were also assessed. Both intent-to-treat and per-protocol analyses were employed.ResultsFor BMD, no intent-to-treat analyses were statistically significant; however, per protocol analyses (i.e., only including TC participants who completed ≥ 75% training requirements) of femoral neck BMD changes were significantly different between TC and UC (+0.04 vs. -0.98%; P = 0.05). Changes in bone formation markers and physical domains of quality of life were also more favorable in per protocol TC vs. UC (P = 0.05). Changes in sway parameters were significantly improved by TC vs. UC (average sway velocity, P = 0.027; anterior-posterior sway range, P = 0.014). Clinical measures of balance and function showed non-significant trends in favor of TC.ConclusionsTC training offered through existing community-based programs is a safe, feasible, and promising intervention for reducing multiple fracture risks. Our results affirm the value of a more definitive, longer-term trial of TC for osteopenic women, adequately powered to detect clinically relevant effects of TC on attenuation of BMD loss and reduction of fall risk in this population.Trial RegistrationClinicalTrials.gov: NCT01039012

Using Wearable Sensors to Monitor Physical Activities of Patients with COPD: A Comparison of Classifier Performance

Chronic obstructive pulmonary disease (COPD) is a major public health problem. Early detection and treatment of an exacerbation in the outpatient setting are important to prevent worsening of clinical status and need for emergency room care or hospital admission. In this study we use accelerometers to capture motion data; and heart rate and respiration rate to capture physiological responses from patients with COPD as they perform a range of Activities of Daily Living (ADL) and physical exercises. We present a comparative analysis of classification performance of a set of different classification techniques and factors that affect classification performance for activity recognition based on accelerometer data. This is the first step towards building a wearable sensor monitoring system for tracking changes in physiological responses of patients with COPD with respect to their physical activity level.

Longitudinal monitoring of patients with Parkinson's disease via wearable sensor technology in the home setting

Objective longitudinal monitoring of symptoms related motor fluctuations can provide valuable information for the clinical management of patients with Parkinsons disease. Current methods for long-term monitoring of motor fluctuations, such as patient diaries, are ineffective due to their time consuming and subjective nature. Researchers have shown that wearable sensors such as accelerometers can be used to gather objective information about a patients motor symptoms. In this paper, we present preliminary results from our analysis on wearable sensor data gathered during longitudinal monitoring of 5 patients with PD. Our results indicate that it is possible to track longitudinal changes in motor symptoms by training a regression model based on Random Forests.

Detecting epileptic seizures using wearable sensors

Epileptic seizures usually consist of stereotyped motor movements in association with characteristic changes in the electroencephalogram (EEG). Accurate recognition and quantification of seizures in patients with epilepsy is essential for diagnosis, selection of treatment and assessing the effects of therapy. In this paper, we present some preliminary results from our on-going research study on using wearable sensors to detect epileptic seizures. Examples are presented from data recorded on one patient.

Comparing a passive-elastic and a powered prosthesis in transtibial amputees

Passive-elastic foot prostheses cannot produce net work. Consequently, passive-elastic foot prostheses are limited in their ability to enable a biologically-realistic gait pattern in transtibial amputees. This shortcoming results in difficulties in balance and walking and leads to high levels of oxygen consumption during locomotion. A powered prosthesis has the potential for overcoming these problems and allowing transtibial amputees to achieve a biologically-realistic gait pattern. In this study, we compared the effects of the Ceterus by Össur, a traditional passive-elastic prosthesis, with those of the PowerFoot Biom (iWalk, Cambridge, MA), a recently-developed powered prosthesis. Gait biomechanics and metabolic cost were compared in a group of 5 transtibial amputees during level-ground walking. The results provided preliminary evidence that the use of a powered prosthesis leads to a decrease in the level of oxygen consumption during ambulation due to improvements in ankle kinematics and kinetics primarily during late stance. An average decrease in oxygen consumption of 8.4% was observed during the study when subjects used the PowerFoot compared to the Ceterus. An average increase of 54% was observed in the peak ankle power generation during late stance. Our results suggest that powered prostheses have the potential for significantly improving ambulation in transtibial amputees.

A Preliminary Assessment of a Novel Pneumatic Unloading Knee Brace on the Gait Mechanics of Patients With Knee Osteoarthritis

To determine whether a knee brace incorporating inflatable air bladders can alter the net peak external knee adduction moment in persons with medial compartment knee osteoarthritis.

A novel sensorized shoe system to classify gait severity in children with cerebral palsy

The clinical management of children with Cerebral Palsy (CP) relies upon periodic assessments of changes in the severity of gait deviations in response to clinical interventions. Current clinical practice is limited to sporadic assessments in a clinical environment and hence it is limited in its ability to estimate the impact of CP-related gait deviations in real-life conditions. Frequent home-based quantitative assessments of the severity of gait deviations would be extremely useful in scheduling clinical visits and gathering feedback about the effectiveness of intervention strategies. The use of a wearable system would allow clinicians to gather information about the severity of gait deviations in the home setting. In this paper, we present ActiveGait, a novel sensorized shoe-based system for monitoring gait deviations. The ActiveGait system was used to gather data, under supervised and unsupervised conditions, from a group of 11 children with various levels of CP-related gait deviation severities. We present a methodology to derive severity measures based on features extracted from Center of Pressure (CoP) trajectories. Results show that a Random Forest classifier is able to estimate severity scores based on the Edinburgh Visual Scale with a level of accuracy >;80% adequate for clinical use.

A sensorized glove for hand rehabilitation

Sensorized garments represent a breakthrough in wearable sensor technology. Sensorized garments have potential for the development of exciting new applications in rehabilitation. In this paper, we present our work toward the development of a system based on a sensorized glove that tracks hand movements during hand grasp/release tasks. The project aims at developing technology to facilitate the implementation of rehabilitation protocols focused on improving hand function. Preliminary results presented in this paper show that the sensorized glove can reliably track hand aperture during static and dynamic tasks.

Optimizing deep brain stimulation settings using wearable sensing technology

Parkinsons disease is a neurodegenerative movement disorder resulting in rigidity, bradykinesia (slowness), tremor and gait disorder. Deep brain stimulation (DBS) of the subthalamic nucleus has been shown to be effective in managing symptoms, but quantitative methods to facilitate the adjustment of the stimulator settings are needed. In this paper, we present preliminary results from a study aimed at investigating the use of wearable sensors to quantitatively track changes in the severity of symptoms in patients with Parkinsons disease undergoing programming of the stimulator. We developed a technique that relies upon features derived from wearable sensors to track changes in the severity of symptoms over a period during which patients motor activities are monitored. Preliminary results indicate that wearable sensors could be utilized to help clinicians achieve optimal settings of the stimulator by providing quantitative feedback concerning the impact of different settings on the severity of Parkinsonian symptoms.

Assessing the feasibility of classifying toe-walking severity in children with cerebral palsy using a sensorized shoe

The clinical management of children with cerebral palsy (CP) relies on monitoring changes in the severity of gait abnormalities and on planning appropriate clinical interventions. Currently available technology does not make it possible to perform clinical gait evaluations as often as it would be desirable from a clinical standpoint. The use of wearable technology (e.g. a sensorized shoe) could provide an effective means to monitor changes in the severity of gait abnormalities in children with CP. In this paper, we studied a group of children with CP who showed an equinus (i.e. toe-walking) gait pattern, a gait abnormality often observed in children with CP. The aim of the study was to determine the feasibility of relying upon a sensorized shoe to assess changes in the severity of toe-walking. We demonstrated that it is possible to use features extracted from the center of pressure trajectory and ankle kinematics to predict the severity of toe-walking. Our results motivate the development and clinical testing of a sensorized shoe to assess changes in gait patterns that accompany the development, and the response to clinical interventions, of children with CP.