Person:

Bonato, Paolo

The aim of this review paper is to summarize recent developments in the field of wearable sensors and systems that are relevant to the field of rehabilitation. The growing body of work focused on the application of wearable technology to monitor older adults and subjects with chronic conditions in the home and community settings justifies the emphasis of this review paper on summarizing clinical applications of wearable technology currently undergoing assessment rather than describing the development of new wearable sensors and systems. A short description of key enabling technologies (i.e. sensor technology, communication technology, and data analysis techniques) that have allowed researchers to implement wearable systems is followed by a detailed description of major areas of application of wearable technology. Applications described in this review paper include those that focus on health and wellness, safety, home rehabilitation, assessment of treatment efficacy, and early detection of disorders. The integration of wearable and ambient sensors is discussed in the context of achieving home monitoring of older adults and subjects with chronic conditions. Future work required to advance the field toward clinical deployment of wearable sensors and systems is discussed.

The development of miniature sensors that can be unobtrusively attached to the body or can be part of clothing items, such as sensing elements embedded in the fabric of garments, have opened countless possibilities of monitoring patients in the field over extended periods of time. This is of particular relevance to the practice of physical medicine and rehabilitation. Wearable technology addresses a major question in the management of patients undergoing rehabilitation, i.e. have clinical interventions a significant impact on the real life of patients? Wearable technology allows clinicians to gather data where it matters the most to answer this question, i.e. the home and community settings. Direct observations concerning the impact of clinical interventions on mobility, level of independence, and quality of life can be performed by means of wearable systems. Researchers have focused on three main areas of work to develop tools of clinical interest: 1)the design and implementation of sensors that are minimally obtrusive and reliably record movement or physiological signals, 2)the development of systems that unobtrusively gather data from multiple wearable sensors and deliver this information to clinicians in the way that is most appropriate for each application, and 3)the design and implementation of algorithms to extract clinically relevant information from data recorded using wearable technology. Journal of NeuroEngineering and Rehabilitation has devoted a series of articles to this topic with the objective of offering a description of the state of the art in this research field and pointing to emerging applications that are relevant to the clinical practice in physical medicine and rehabilitation.

Background: Prefabricated orthotic devices are currently designed to fit a range of patients and therefore they do not provide individualized comfort and function. Custom-fit orthoses are superior to prefabricated orthotic devices from both of the above-mentioned standpoints. However, creating a custom-fit orthosis is a laborious and time-intensive manual process performed by skilled orthotists. Besides, adjustments made to both prefabricated and custom-fit orthoses are carried out in a qualitative manner. So both comfort and function can potentially suffer considerably. A computerized technique for fabricating patient-specific orthotic devices has the potential to provide excellent comfort and allow for changes in the standard design to meet the specific needs of each patient. Methods: In this paper, 3D laser scanning is combined with rapid prototyping to create patient-specific orthoses. A novel process was engineered to utilize patient-specific surface data of the patient anatomy as a digital input, manipulate the surface data to an optimal form using Computer Aided Design (CAD) software, and then download the digital output from the CAD software to a rapid prototyping machine for fabrication. Results: Two AFOs were rapidly prototyped to demonstrate the proposed process. Gait analysis data of a subject wearing the AFOs indicated that the rapid prototyped AFOs performed comparably to the prefabricated polypropylene design. Conclusions: The rapidly prototyped orthoses fabricated in this study provided good fit of the subject's anatomy compared to a prefabricated AFO while delivering comparable function (i.e. mechanical effect on the biomechanics of gait). The rapid fabrication capability is of interest because it has potential for decreasing fabrication time and cost especially when a replacement of the orthosis is required.

Background: Post-menopausal osteopenic women are at increased risk for skeletal fractures. Current osteopenia treatment guidelines include exercise, however, optimal exercise regimens for attenuating bone mineral density (BMD) loss, or for addressing other fracture-related risk factors (e.g. poor balance, decreased muscle strength) are not well-defined. Tai Chi is an increasingly popular weight bearing mind-body exercise that has been reported to positively impact BMD dynamics and improve postural control, however, current evidence is inconclusive. This study will determine the effectiveness of Tai Chi in reducing rates of bone turnover in post-menopausal osteopenic women, compared with standard care, and will preliminarily explore biomechanical processes that might inform how Tai Chi impacts BMD and associated fracture risks. Methods/Design: A total of 86 post-menopausal women, aged 45-70y, T-score of the hip and/or spine -1.0 and -2.5, have been recruited from primary care clinics of a large healthcare system based in Boston. They have been randomized to a group-based 9-month Tai Chi program plus standard care or to standard care only. A unique aspect of this trial is its pragmatic design, which allows participants randomized to Tai Chi to choose from a pre-screened list of community-based Tai Chi programs. Interviewers masked to participants' treatment group assess outcomes at baseline and 3 and 9 months after randomization. Primary outcomes are serum markers of bone resorption (C-terminal cross linking telopeptide of type I collagen), bone formation (osteocalcin), and BMD of the lumbar spine and proximal femur (dual-energy X-ray absorptiometry). Secondary outcomes include health-related quality-of-life, exercise behavior, and psychological well-being. In addition, kinetic and kinematic characterization of gait, standing, and rising from a chair are assessed in subset of participants (n = 16) to explore the feasibility of modeling skeletal mechanical loads and postural control as mediators of fracture risk. Discussion: Results of this study will provide preliminary evidence regarding the value of Tai Chi as an intervention for decreasing fracture risk in osteopenic women. They will also inform the feasibility, value and potential limitations related to the use of pragmatic designs for the study of Tai Chi and related mind-body exercise. If the results are positive, this will help focus future, more in-depth, research on the most promising potential mechanisms of action identified by this study. Trial registration: This trial is registered in Clinical Trials.gov, with the ID number of NCT01039012.

Background: Tai 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 TC's potential to reduce bone loss and improve fall-predictive balance parameters in osteopenic women. Methods: In 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. Results: For BMD, no intent-to-treat analyses were statistically significant; however, per protocol analyses (i.e., only including TC participants who completed (\geq) 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. Conclusions: TC 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.

Mobility technologies, including wheelchairs, prostheses, joint replacements, assistive devices, and therapeutic exercise equipment help millions of people participate in desired life activities. Yet, these technologies are not yet fully transformative because many desired activities cannot be pursued or are difficult to pursue for the millions of individuals with mobility related impairments. This WTEC study, initiated and funded by the National Science Foundation, was designed to gather information on European innovations and trends in technology that might lead to greater mobility for a wider range of people. What might these transformative technologies be and how might they arise? Based on visits to leading mobility technology research labs in western Europe, the WTEC panel identified eight major trends in mobility technology research. This commentary summarizes these trends, which are then described in detail in companion papers appearing in this special issue.

Background: Compensating for the effect of gravity by providing arm-weight support (WS) is a technique often utilized in the rehabilitation of patients with neurological conditions such as stroke to facilitate the performance of arm movements during therapy. Although it has been shown that, in healthy subjects as well as in stroke survivors, the use of arm WS during the performance of reaching movements leads to a general reduction, as expected, in the level of activation of upper limb muscles, the effects of different levels of WS on the characteristics of the kinematics of motion and of the activity of upper limb muscles have not been thoroughly investigated before. Methods: In this study, we systematically assessed the characteristics of the kinematics of motion and of the activity of 14 upper limb muscles in a group of 9 healthy subjects who performed 3-D arm reaching movements while provided with different levels of arm WS. We studied the hand trajectory and the trunk, shoulder, and elbow joint angular displacement trajectories for different levels of arm WS. Besides, we analyzed the amplitude of the surface electromyographic (EMG) data collected from upper limb muscles and investigated patterns of coordination via the analysis of muscle synergies. Results: The characteristics of the kinematics of motion varied across WS conditions but did not show distinct trends with the level of arm WS. The level of activation of upper limb muscles generally decreased, as expected, with the increase in arm WS. The same eight muscle synergies were identified in all WS conditions. Their level of activation depended on the provided level of arm WS. Conclusions: The analysis of muscle synergies allowed us to identify a modular organization underlying the generation of arm reaching movements that appears to be invariant to the level of arm WS. The results of this study provide a normative dataset for the assessment of the effects of the level of arm WS on muscle synergies in stroke survivors and other patients who could benefit from upper limb rehabilitation with arm WS.

Background: Advances in miniature sensor technology have led to the development of wearable systems that allow one to monitor motor activities in the field. A variety of classifiers have been proposed in the past, but little has been done toward developing systematic approaches to assess the feasibility of discriminating the motor tasks of interest and to guide the choice of the classifier architecture. Methods: A technique is introduced to address this problem according to a hierarchical framework and its use is demonstrated for the application of detecting motor activities in patients with chronic obstructive pulmonary disease (COPD) undergoing pulmonary rehabilitation. Accelerometers were used to collect data for 10 different classes of activity. Features were extracted to capture essential properties of the data set and reduce the dimensionality of the problem at hand. Cluster measures were utilized to find natural groupings in the data set and then construct a hierarchy of the relationships between clusters to guide the process of merging clusters that are too similar to distinguish reliably. It provides a means to assess whether the benefits of merging for performance of a classifier outweigh the loss of resolution incurred through merging. Results: Analysis of the COPD data set demonstrated that motor tasks related to ambulation can be reliably discriminated from tasks performed in a seated position with the legs in motion or stationary using two features derived from one accelerometer. Classifying motor tasks within the category of activities related to ambulation requires more advanced techniques. While in certain cases all the tasks could be accurately classified, in others merging clusters associated with different motor tasks was necessary. When merging clusters, it was found that the proposed method could lead to more than 12% improvement in classifier accuracy while retaining resolution of 4 tasks. Conclusion: Hierarchical clustering methods are relevant to developing classifiers of motor activities from data recorded using wearable systems. They allow users to assess feasibility of a classification problem and choose architectures that maximize accuracy. By relying on this approach, the clinical importance of discriminating motor tasks can be easily taken into consideration while designing the classifier.

Advances in neuroscience and biomedical engineering deeply affect the clinical practice of physical medicine & rehabilitation. New research findings and engineering tools are continuously made available that have the potential of dramatically enhancing the ability of clinicians to design effective rehabilitation interventions. This quickly evolving research field is difficult to track because related literature appears in a wide range of scientific journals. There is a need for a scientific journal that offers to its readership a forum at the intersection of neuroscience, biomedical engineering, and physical medicine & rehabilitation. The Journal of NeuroEngineering and Rehabilitation (JNER) is intended to fill this gap and foster cross-fertilizations among these disciplines. By making readily available to clinicians selected studies with potential impact on physical medicine & rehabilitation, JNER is anticipated to foster the development of novel and more effective rehabilitation strategies. Conversely, by presenting clinical problems to a readership of neuroscientists and engineers, JNER is expected to generate innovative work in neuroscience and biomedical engineering with future applications to physical medicine & rehabilitation. JNER will leverage on Open Access as a means to guarantee that its content is readily available to scientists, clinicians, and the general public thus promoting scientific and technological advances that are relevant to rehabilitation. JNER is an Open Access initiative. Open Access assures dissemination to the widest possible audience and is seen by many as essential for publicly funded research. BioMed Central offers an outstanding platform to make JNER possible and allow neuroscientists, biomedical engineers, and clinicians to see their work published in a timely manner and thus make an immediate impact in the field of rehabilitation. JNER will focus on innovative work with higher likelihood of a dramatic impact on rehabilitation. Thus, priority will be given to outstanding and visionary scientific reports, i.e. those proposing exceptionally innovative concepts with great potential in the field.