Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems

A Proposal for New Algorithm that Defines Gait-Induced Acceleration and Gait Cycle in Daily Parkinsonian Gait Disorders

We developed a new device, the portable gait rhythmogram (PGR), to record up to 70 hrs of movement-induced accelerations. Acceleration values induced by various movements, averaged every 10 min, showed gamma distribution, and the mean value of this distribution was used as an index of the amount of overall movements. Furthermore, the PGR algorithm can specify gait-induced accelerations using the pattern-matching method. Analysis of the relationship between gait-induced accelerations and gait cycle duration makes it possible to quantify Parkinson’s disease (PD)-specific pathophysiological mechanisms underlying gait disorders. Patients with PD showed the following disease-specific patterns: (1) reduced amount of overall movements and (2) low amplitude of gait-induced accelerations in the early stages of the disease, which was compensated by fast stepping. Loss of compensation was associated with slow stepping gait, (3) narrow range of gait-induced acceleration amplitude and gait cycle duration, suggesting monotony, and (4) evident motor fluctuations during the day by tracing changes in the above two parameters. Prominent motor fluctuation was associated with frequent switching between slow stepping mode and active mode. These findings suggest that monitoring various movement- and gait-induced accelerations allows the detection of specific changes in PD. We conclude that continuous long-term monitoring of these parameters can provide accurate quantitative assessment of parkinsonian clinical motor signs

Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials

A Review on Accelerometry-Based Gait Analysis and Emerging Clinical Applications

Gait analysis continues to be an important technique for many clinical applications to diagnose and monitor certain diseases. Many mental and physical abnormalities cause measurable differences in a person's gait. Gait analysis has applications in sport, computer games, physical rehabilitation, clinical assessment, surveillance, human recognition, modelling, and many other fields. There are established methods using various sensors for gait analysis, of which, accelerometers are one of the most often employed. Accelerometer sensors are generally more user friendly and less invasive. In this paper, we review research regarding accelerometer sensors used for gait analysis with particular focus on clinical applications. We provide a brief introduction to accelerometer theory followed by other popular sensing technologies. The commonly used gait phases and parameters are enumerated. The details of extracting the papers for review are provided. We also review several gait analysis software. Then, we provide an extensive report of accelerometry based gait analysis systems and applications with additional emphasis on trunk accelerometry. We conclude this review with future research directions

Upper limb function in children with cerebral palsy : range of motion, botulinum neurotoxin A and accelerometry metrics

Cerebral palsy (CP) is the most common cause of movement disorders in children and may result in diverse levels of severity of the disability, from very mild to very severe. The underlying neurological pathology in CP is by definition not progressive, but motor symptoms may cause permanent and progressive secondary movement complications, which often change over time. Movement disorders are a prominent component in individuals with CP and treatments are often aimed at affecting movement disorders. Since CP is caused by a permanent lesion to the brain, the lesion will affect the individual in different ways throughout life and in daily life activities. Thus, it is particularly important to understand how secondary complications develop from early childhood until adulthood in this population. Measurement tools that are evaluating individuals’ daily life need to be psychometrically evaluated, and we also need to evaluate the treatments outcome of the secondary complications within CP efficiently. Gaining more knowledge about secondary complications to CP is a priority in CP research. This thesis focuses on upper limb (UL) passive range of motion (pROM) and contracture development over time, botulinum neurotoxin A (BoNT-A) and on accelerometry based metrics evaluated in daily life in children and adolescents. Upper limb passive range of motion change over time and BoNT-A treatment were investigated by population-based data sourced from the Swedish national CP registry. Upper limb clinical assessments and accelerometry based metrics were obtained from 20 children and adolescents, who were residents of Sörmland or Västmanland in Sweden. Results show that one-third of children and adolescents with CP developed upper limb contractures and the pROM deteriorated over time. The contracture development started already at preschool age. The first and most severe contractures were found in wrist extension with extended fingers. Children with the most affected level of manual ability were at highest risk for contracture development. One-fifth of children with spastic or dyskinetic CP had been treated with BoNT-A in the ULs, 45% of them early at age, 1–3 years. Children with lower levels of manual ability or full pROM with resistance at the end of the movement range were most likely to receive a first UL BoNT-A treatment. At the first treatment occasion, thumb and forearm muscles were the most targeted. Interestingly, a first UL BoNT-A treatment at an early age, 1-3 years implied a favourable pROM development over time compared to children treated first time at a later age, 4-15 years. Early detection of a first sign of muscle shortening and thus early intervention before contractures are manifested can be one of the keys to successful outcomes. In daily life, during sedentary time and light-intensity physical activity, accelerometry metrics provide objective information about UL asymmetry and relative use. Thus, accelerometry metrics may provide complementary information to clinical assessments in daily life

The association of cognitive flexibility with prioritization and gait: A cross-sectional cohort study in healthy older adults

In den letzten Jahren konnte gezeigt werden, dass es eine supraspinale Kontrolle des Gehens gibt. Dieses Netzwerk umfasst neben motorischen Hirnarealen vor allem auch kognitive und limbische Strukturen und deren Projektionen. Dieses supraspinale Netzwerk hat einen wichtigen Einfluss v.a. auf das Verhalten während des Gehens z.B. in Dual Task Situationen. Dual Task Situationen sind sehr alltagsrelevant, da sie häufig vorkommen, z.B. in Form von Sprechen während des Gehens. Defizite in der Dual Task Fähigkeit beeinflussen die Qualität des Gehens und können z.B. zu Stürzen führen. Diese Defizite begründen sich wahrscheinlich auf Störungen der exekutiven Funktionen, wie z.B. kognitive Flexibilität, da diese eine wichtige Rolle in der Steuerung von Dual Task Verhalten spielen. Diese Arbeit besteht aus und diskutiert zwei Publikationen, die sich mit der Assoziation von kognitiver Flexibilität und Priorisierung, sowie kognitiver Flexibilität und quantitativ erhobenen Gangparametern und deren Anpassung bei Dual Task Aufgaben beim Gehen befassen. Für beide Publikationen wurden über 660 gesunde Probanden zwischen 50 und 80 Jahren mit einem Assessment untersucht, das aus vier Single Task Aufgaben (Subtrahieren, Durchführen einer Ankreuzaufgabe, Gehen mit normaler Gehgeschwindigkeit und Gehen mit schneller Gehgeschwindigkeit) und zwei Dual Task Aufgaben (Gehen mit schneller Gehgeschwindigkeit mit gleichzeitigem Durchführen der Ankreuzaufgabe und Gehen mit schneller Gehgeschwindigkeit mit gleichzeitigem Subtrahieren) bestand. Als Maß der kognitiven Flexibilität wurde der Trail Making Test (TMT) durchgeführt. In Publikation 1 wurden die Dual Task Kosten berechnet, die die Leistungsverschlechterung in einer Aufgabe unter Dual Task im Vergleich zur Durchführung der gleichen Aufgabe unter Single Task Bedingungen beschreiben. Die Dual Task Kosten der einzelnen Aufgaben wurden zwischen dem Tertil der Probanden mit der besten und dem Tertil mit der schlechtesten Leistung im TMT verglichen. Es zeigte sich, dass die Probanden mit schlechterer Leistung im TMT die kognitive Aufgabe und nicht das Gehen in der Dual Task Aufgabe Gehen mit schneller Gehgeschwindigkeit mit gleichzeitigem Subtrahieren priorisierten. Die Probanden mit besserer Leistung im TMT hingegen priorisierten die motorische Aufgabe gegenüber dem Subtrahieren. Dies weist auf eine Assoziation zwischen kognitiver Flexibilität und Priorisierung hin. In Publikation 2 wurden quantitative Gangparameter, die mittels eines tragbaren Bewegungssensors erhoben wurden, mit dem Ergebnis des TMT korreliert. Es zeigte sich, dass je schwerer die Gangaufgabe war, desto mehr Gangparameter signifikant mit dem TMT korreliert waren. Die stärkste Korrelation mit dem TMT wurde für den Parameter Gehgeschwindigkeit unter der Aufgabe Gehen mit schneller Gehgeschwindigkeit mit gleichzeitigem Subtrahieren gefunden. Dies unterstützt frühere Arbeiten die der Gehgeschwindigkeit eine hohe Relevanz in der Beschreibung von kognitiven Defiziten zugeordnet haben. Allerdings handelt es ich dabei um einen recht unspezifischen Marker. Zusätzlich wurden die Muster der Veränderungen der einzelnen Gangparameter über die Single Task Aufgabe Gehen mit schneller Gehgeschwindigkeit und die Dual Task Aufgaben Gehen mit schneller Gehgeschwindigkeit mit gleichzeitigem Durchführen der Ankreuzaufgabe und Gehen mit schneller Gehgeschwindigkeit mit gleichzeitigem Subtrahieren zwischen den guten und schlechten Tertial im TMT verglichen. Hierbei zeigten sich unterschiedliche Muster in den Parametern für Gangvariabilität, Gangregularität, und Gangasymmetrie. Die Probanden mit besserer kognitiver Flexibilität scheinen die Strategien zwischen den Aufgaben gewechselt, bzw. an die Aufgaben angepasst zu haben, was die Probanden mit schlechterer kognitiver Flexibilität nur eingeschränkt machten. Zusammengefasst deuten die Ergebnisse darauf hin, dass kognitive Flexibilität wichtig für das Gehen bei älteren Leuten ist und Probanden mit einer schlechteren kognitiven Flexibilität durchaus Probleme haben könnten, das Gehen an herausfordernde Geh-Bedingungen anzupassen. Die Ergebnisse beider Studien zusammen weisen darauf hin, dass kognitive Flexibilität sehr wichtig für das Gehen unter herausfordernden Geh-Situationen ist, wie z.B. Dual Tasking. Unsere Daten weisen auch darauf hin, dass Priorisierung und Adaptationsfähigkeit des Gehens Teil eines komplexen Netzwerkes zwischen Defiziten in kognitiver Flexibilität und Stürzen sind. Es liegt daher nahe, dass Defizite in der Priorisierung und der Anpassung des Gehens an situative Erfordernisse, mögliche und wichtige Mechanismen hierfür sein könnten. Dies sollte jedoch in weiteren Studien gezielt untersucht werden.In recent years, it has been shown that there is a supraspinal network for the control of gait. It consists of motor, cognitive and limbic structures and their projections. These supraspinal networks have an important influence on walking behaviour, e.g., in dual tasking situations. Dual tasking situations are very relevant in everyday life, because they occur very often, e.g. when talking while walking. Deficits in dual tasking can lead to impaired walking and falls. These deficits are most likely driven by deficits in executive functions, such as cognitive flexibility, as they play a particularly important role in the control of dual tasking behaviour. This thesis presents and discusses two publications about the association of cognitive flexibility and prioritization, as well as the association of cognitive flexibility and quantitative gait parameters and their adaptation to dual tasking conditions. In both publications, more than 660 healthy older people, aged between 50 and 80 years, were assessed using four single task conditions (subtracting, checking boxes, walking at convenient speed and walking at fast speed) and two dual task conditions (walking at fast speed with checking boxes and walking at fast speed with subtracting serial 7s). As a measure of cognitive flexibility, the Trail Making Test (TMT) was performed. In publication 1, dual task costs (i.e., the percent decline of task performance under dual tasking compared to single tasking) were calculated. The dual task cost of each task was compared between the tertile of participants with the best (good TMT performers) and of the tertile with the worst (poor TMT performers) performance in the TMT. Under the dual tasking walking while subtracting serial 7s condition, good TMT performers prioritized walking over subtracting. Conversely, poor TMT performers prioritized the subtracting task over walking. These results suggested an association of cognitive flexibility and prioritization. In publication 2, quantitative gait parameters, collected with a wearable sensor-unit, were correlated with performance of the TMT. We found that a higher number of gait parameters were significantly correlated with the TMT when the gait task was more challenging. The strongest correlation was found for walking speed in the dual task walking while subtracting serial 7s condition. This indicates that gait speed is an important gait parameter for the investigation of the association of cognitive flexibility with gait, although the parameter is obviously unspecific. In addition, patterns of differences of gait parameters across the conditions of single task walking at fast speed and dual task walking while checking boxes and dual task walking while subtracting serial 7s were compared between good and poor TMT performers. Here, we found different patterns across conditions in the parameters gait variability, phase coordination index, and gait asymmetry. Subjects with good cognitive flexibility seem to switch or adapt strategies between tasks, while participants with poorer cognitive flexibility have limited resources for these adaptations. The findings of this analysis also suggest that cognitive flexibility is important for walking in older adults, and people with poor cognitive flexibility have deficits in adapting walking to challenging walking conditions. The results of both studies suggest that cognitive flexibility is an important contributor to safe walking, especially under challenging walking conditions, e.g., dual tasking. We hypothesize that prioritization and adaptation mechanisms of gait are parts of a complex interaction network between cognitive flexibility (deficits) and falls. This should be investigated in more detail in further studies

The role of mobile technology for fall risk assessment for individuals with multiple sclerosis

Multiple Sclerosis (MS) is a chronic, progressive neurogenerative disease that affects one million people in the United States (Wallin et al., 2019). Common MS symptoms include impaired coordination, poor walking and balance, and fatigue, and these symptoms put people with MS (pwMS) at a higher risk for falls (Cameron & Nilsagard, 2018). Falls are highly prevalent among pwMS and can result in detrimental consequences including bone fractures and even death (Matsuda et al., 2011). To prevent falls and fall related injuries, it is important to first assess for multiple risk factors and then intervene through targeted treatments (Palumbo et al., 2015). Fall risk can be assessed through self-report measures, clinical performance tests, or with technology such as force plates and motion capture systems (Kanekar & Aruin, 2013). However, clinicians have time constraints, technology is expensive, and trained personnel is needed. Moreover, due to the COVID-19 pandemic, access to in-person clinical visits is limited. As a result, pwMS may not receive fall risk screening and remain vulnerable to fall related injuries. Mobile technology offers a solution to increase access to fall risk screening using an affordable, ubiquitous, and portable tool (Guise et al., 2014; Marrie et al., 2019). Therefore, the overarching goal of this study was to develop a usable fall risk health application (app) for pwMS to self-assess their fall risk in the home setting. Four studies were performed: 1) smartphone accelerometry was tested to measure postural control in pwMS; 2) a fall risk algorithm was developed for a mobile health app; 3) a fall risk app, Steady-MS, was developed and its usability was tested; and 4) the feasibility of home-based procedures for using Steady-MS was determined. Results suggest that smartphone accelerometry can assess postural control in pwMS. This information was used to develop an algorithm to measure overall fall risk in pwMS and was then incorporated into Steady-MS. Steady-MS was found to be usable among MS users and feasible to use in the home setting. The results from this project demonstrate that pwMS can independently assess their fall risk with Steady-MS in their homes. For the first time, pwMS are equipped to self-assess their fall risk and can monitor and manage their risk. Home-based assessments also opens the potential to offer individualized and targeted treatments to prevent falls. Ultimately, Steady-MS increases access to home-based assessments to reduce falls and improve functional independence for those with MS

Sensor Technologies to Manage the Physiological Traits of Chronic Pain: A Review

Non-oncologic chronic pain is a common high-morbidity impairment worldwide and acknowledged as a condition with significant incidence on quality of life. Pain intensity is largely perceived as a subjective experience, what makes challenging its objective measurement. However, the physiological traces of pain make possible its correlation with vital signs, such as heart rate variability, skin conductance, electromyogram, etc., or health performance metrics derived from daily activity monitoring or facial expressions, which can be acquired with diverse sensor technologies and multisensory approaches. As the assessment and management of pain are essential issues for a wide range of clinical disorders and treatments, this paper reviews different sensor-based approaches applied to the objective evaluation of non-oncological chronic pain. The space of available technologies and resources aimed at pain assessment represent a diversified set of alternatives that can be exploited to address the multidimensional nature of pain.Ministerio de Economía y Competitividad (Instituto de Salud Carlos III) PI15/00306Junta de Andalucía PIN-0394-2017Unión Europea "FRAIL

Computational neurorehabilitation: modeling plasticity and learning to predict recovery

Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling – regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity