Kinect-based Solution for the Home Monitoring of Gait and Balance in Elderly People with and without Neurological Diseases

Alterations of gait and balance are a significant cause of falls, injuries, and consequent hospitalizations in the elderly. In addition to age-associated motor decline, other factors can impact gait and stability, including the motor dysfunctions caused by neurological diseases such as Parkinson’s disease or hemiplegia after stroke. Monitoring changes and deterioration in gait patterns and balance is crucial for activating rehabilitation treatments and preventing serious consequences. This work presents a Kinect-based solution, suitable for domestic contexts, for assessing gait and balance in individuals at risk of falling. The system captures body movements during home acquisition sessions scheduled by clinicians at definite times of the day and automatically estimates specific functional parameters to objectively characterize the subjects’ performance. The system includes a graphical user interface designed to ensure usability in unsupervised contexts: the human-computer interaction mainly relies on natural body movements to support the self-management of the system, if the motor conditions allow it. This work presents the system’s features and facilities, and the preliminary results on healthy volunteers’ trials

Phase Dynamics in Human Visuomotor Control - Health & Disease

In this thesis, comprised of four publications, I investigated phase dynamics of visuomotor control in humans during upright stance in response to an oscillatory visual drive. For this purpose, I applied different versions of a ‘moving room’ paradigm in virtual reality while stimulating human participants with anterior-posterior motion of their visual surround and analyzed their bodily responses. Human balance control constitutes a complex interplay of interdependent processes. The main sensory contributors include vision, vestibular input, and proprioception, with a dominant role attributed to vision. The purpose of the balance control system is to keep the body’s center of mass (COM) within a certain spatial range around the current base of support. Ever-changing environmental circumstances along with sensory noise cause the body to permanently sway around its point of equilibrium. Considering this sway, the human body can be modelled as a (multi-link) inverted pendulum. To maintain balance while being exposed to perturbations of the visual environment, humans adjust their sway to counteract the perceived motion of their bodies. Neurodegenerative diseases like Parkinson’s impair balance control and thus are likely to affect these mechanisms. Hence, investigation of bodily responses to a visual drive gives insight into visuomotor control in health and disease. In my first study, I introduced inter-trial phase coherence (ITPC) as a novel method to investigate postural responses to periodical visual stimulation. I found that human participants phase-locked the motion of their center of pressure (COP) to a 3-D dot cloud which oscillated in the anterior-posterior direction. This effect was equally strong for a low frequency of visual stimulation at 0.2 Hz and a high frequency of 1.5 Hz, the latter exceeding the previously assumed frequency range associated with coherent postural sway responses to periodical oscillations of the visual environment (moving room). Moreover, I was able to show that ITPC reliably captured responses in almost all participants, thereby addressing the common problem of inter-subject variability in body sway research. Based on the results of my first study, I concluded phase locking to be an essential feature in human postural control. For the second study, I introduced a mobile and cost-effective setup to apply a visual paradigm consisting of a virtual tunnel which stretched in the anterior-posterior direction and oscillated back and forth at three distinct frequencies (0.2 Hz, 0.8 Hz, and 1.2 Hz). Because tracking of the COP alone neglects crucial information about how COM shifts are arranged across the body, I included additional full-body motion tracking here to evaluate sway of individual body segments. Using a modified measure of phase locking, the phase locking value (PLV), allowed me to find participants phase-locking not only their COP, but also additional segments of their body to the visual drive. While their COP exhibited a strong phase locking to all frequencies of visual stimulation, distribution of phase locking across the body underwent a shift as the frequency of the visual stimulation increased. For the lowest frequency of 0.2 Hz, participants phase-locked almost their entire body to the stimulus. At higher frequencies, this phase locking shifted towards the lower torso and hip, with subjects almost exclusively phase-locking their hip to the visual drive at the highest frequency of 1.2 Hz. Having introduced a novel and reliable measurement along with a mobile setup, these results allowed me to empirically confirm shifts in postural strategies previously proposed in the literature. In the third study, a collaboration with the neurology department of the Universitätsklinikum Gießen und Marburg (UKGM), I used the same setup and paradigm as in the previous study and additionally derived the trajectory of the COM from a weighted combination of certain body segments. The aim was to investigate phase locking of body sway in a group of patients suffering from Parkinson’s disease (PD) to find potential means for an early diagnosis of the illness. For this purpose, I recruited a group of PD patients, an age-matched control group, and a group of young healthy adults. Even though the sway amplitude of PD patients was significantly larger than that of both other groups, they phase-locked their COP and COM in a similar manner as the control groups. However, considering individual body segments, the shift in PLV distribution differed between groups. While young healthy adults, analogous to the participants in the second study, exhibited a shift towards exclusive phase locking of their hips as frequency of the stimulation increased, both PD patients and age-matched controls maintained a rather homogeneous phase locking across their body. This suggested increased body stiffness, although being an effect of age rather than disease. Overall, I concluded that patients of early-to-mid stage PD exhibit impaired motor control, reflected in their increased sway amplitude, but intact visuomotor processing, indicated by their ability to phase-lock the motion of their body to a visual drive. The fourth study, to which I contributed as second author, used experimental data collected from an additional visual condition in the course of the third study. This condition consisted of unpredictable back and forward motion of the simulated tunnel. Here, we investigated the velocity profiles of the COP and COM in response to the unpredictable visual motion and a baseline condition at which the tunnel remained static. We found PD patients to exhibit larger velocities of their COP and COM under both conditions when compared to the control groups. When examining the net increase that unpredictable motion had on the velocity of both parameters, we found a significantly higher increase in COP velocity for both PD patients and age-matched controls, but no increase in COM velocity in any of the groups. These results suggested that all groups successfully maintained their balance under unpredictable visual perturbations, but that PD patients and older adults required more effort to accomplish this task, as reflected by the increased velocity of their COP. Again, these results indicated an effect of age rather than disease on the observed postural responses. In summary, using innovative phase-locking techniques and simultaneously tracking multiple body sway parameters, I was able to provide novel insight into visuomotor control in humans. First, I overcame previous issues of inconsistent sway parameters in groups of participants; Second, I found phase-locking to be an essential feature of visuomotor processing, which also allowed me to empirically confirm previously established theories of postural control; Third, through studies in collaboration with the neurology department of the UKGM, I was able to uncover new aspects of visuomotor processing in Parkinson’s, contributing to a better understanding of the sensorimotor aspects of the disease

Design, Development and Testing of a Balance Board with Variable Torsional Stiffness and Time Delay

The ability to balance and maintain upright posture can decline for a variety of reasons, such as aging and neuromuscular impairment. As the ability to balance declines, the risk of falling increases. Falls are a major cause of injury, and often lead to a dramatic decline in quality of life. Currently, to alleviate balance deficiencies, people participate in balance training, which most commonly refers to standing on an unstable balance board; the most common boards used are either passive wobble boards, or more advanced commercial systems such as the Biodex System SD ® or the Neurocom SMART Balance Master® . Balance training has been shown to improve both static posture and dynamic balance; however, the current methodologies only utilize stiffness and force control. It has been shown that there are two distinct mechanisms of loss of postural instability: forward/back leaning, arising from insufficient postural stiffness or decreased neuromuscular gain, and limit cycle oscillations, which arise from excessive time delay in the neuromuscular system. We have created a balance board able to elicit both mechanisms of instability, which can be achieved through two controllable parameters: torsional stiffness and haptic feedback time delay. In addition to building a functional balance board, a safety platform was also fabricated which ensures both user safety and comfort. After careful calibration of the balance board and the systems used to gather data, initial human testing was performed. Three major tests were completed: discrete step stiffness, linear ramping stiffness, and variable time delay. These tests confirmed that the balance board system is capable of utilizing both mechanisms of instability; both forward/backward leaning and limit cycle oscillations we observed in all participants. These initial results are promising, and lead directly into a variety of different options for testing on the balance board. The board can be used to test various populations including athletes, older adults, and people with neuromuscular disorders. The ultimate goal of this balance board would be to create a balance score that can be compared among populations, to use the board for training, and to convert this balance board to a robotic platform that creates individualized training plans for users. This novel balance board system has created a large range of possibilities for the future of balance studies and training

Feasibility and acceptability of an exergame intervention for schizophrenia

Objectives To evaluate the feasibility and acceptability of an exergame intervention as a tool to promote physical activity in outpatients with schizophrenia. Design Feasibility/Acceptability Study and Quasi-Experimental Trial. Method Sixteen outpatients with schizophrenia received treatment as usual and they all completed an 8-week exergame intervention using Microsoft Kinect® (20 min sessions, biweekly). Participants completed pre and post treatment assessments regarding functional mobility (Timed Up and Go Test), functional fitness performance (Senior Fitness Test), motor neurological soft signs (Brief Motor Scale), hand grip strength (digital dynamometer), static balance (force plate), speed of processing (Trail Making Test), schizophrenia-related symptoms (Positive and Negative Syndrome Scale) and functioning (Personal and Social Performance Scale). The EG group completed an acceptability questionnaire after the intervention. Results Attrition rate was 18.75% and 69.23% of the participants completed the intervention within the proposed schedule. Baseline clinical traits were not related to game performance indicators. Over 90% of the participants rated the intervention as satisfactory and interactive. Most participants (76.9%) agreed that this intervention promotes healthier lifestyles and is an acceptable alternative to perform physical activity. Repeated-measures MANOVA analyses found no significant multivariate effects for combined outcomes. Conclusion This study established the feasibility and acceptability of an exergame intervention for outpatients with schizophrenia. The intervention proved to be an appealing alternative to physical activity. Future trials should include larger sample sizes, explore patients' adherence to home-based exergames and consider greater intervention dosage (length, session duration, and/or frequency) in order to achieve potential effects

Using the Microsoft Kinect to assess human bimanual coordination

Optical marker-based systems are the gold-standard for capturing three-dimensional (3D) human kinematics. However, these systems have various drawbacks including time consuming marker placement, soft tissue movement artifact, and are prohibitively expensive and non-portable. The Microsoft Kinect is an inexpensive, portable, depth camera that can be used to capture 3D human movement kinematics. Numerous investigations have assessed the Kinect\u27s ability to capture postural control and gait, but to date, no study has evaluated it\u27s capabilities for measuring spatiotemporal coordination. In order to investigate human coordination and coordination stability with the Kinect, a well-studied bimanual coordination paradigm (Kelso, 1984, Kelso; Scholz, & Schöner, 1986) was adapted. ^ Nineteen participants performed ten trials of coordinated hand movements in either in-phase or anti-phase patterns of coordination to the beat of a metronome which was incrementally sped up and slowed down. Continuous relative phase (CRP) and the standard deviation of CRP were used to assess coordination and coordination stability, respectively.^ Data from the Kinect were compared to a Vicon motion capture system using a mixed-model, repeated measures analysis of variance and intraclass correlation coefficients (2,1) (ICC(2,1)).^ Kinect significantly underestimated CRP for the the anti-phase coordination pattern (p \u3c.0001) and overestimated the in-phase pattern (p\u3c.0001). However, a high ICC value (r=.097) was found between the systems. For the standard deviation of CRP, the Kinect exhibited significantly higher variability than the Vicon (p \u3c .0001) but was able to distinguish significant differences between patterns of coordination with anti-phase variability being higher than in-phase (p \u3c .0001). Additionally, the Kinect was unable to accurately capture the structure of coordination stability for the anti-phase pattern. Finally, agreement was found between systems using the ICC (r=.37).^ In conclusion, the Kinect was unable to accurately capture mean CRP. However, the high ICC between the two systems is promising and the Kinect was able to distinguish between the coordination stability of in-phase and anti-phase coordination. However, the structure of variability as movement speed increased was dissimilar to the Vicon, particularly for the anti-phase pattern. Some aspects of coordination are nicely captured by the Kinect while others are not. Detecting differences between bimanual coordination patterns and the stability of those patterns can be achieved using the Kinect. However, researchers interested in the structure of coordination stability should exercise caution since poor agreement was found between systems

Technological advancements in the analysis of human motion and posture management through digital devices

Technological development of motion and posture analyses is rapidly progressing, especially in rehabilitation settings and sport biomechanics. Consequently, clear discrimination among different measurement systems is required to diversify their use as needed. This review aims to resume the currently used motion and posture analysis systems, clarify and suggest the appropriate approaches suitable for specific cases or contexts. The currently gold standard systems of motion analysis, widely used in clinical settings, present several limitations related to marker placement or long procedure time. Fully automated and markerless systems are overcoming these drawbacks for conducting biomechanical studies, especially outside laboratories. Similarly, new posture analysis techniques are emerging, often driven by the need for fast and non-invasive methods to obtain high-precision results. These new technologies have also become effective for children or adolescents with non-specific back pain and postural insufficiencies. The evolutions of these methods aim to standardize measurements and provide manageable tools in clinical practice for the early diagnosis of musculoskeletal pathologies and to monitor daily improvements of each patient. Herein, these devices and their uses are described, providing researchers, clinicians, orthopedics, physical therapists, and sports coaches an effective guide to use new technologies in their practice as instruments of diagnosis, therapy, and prevention

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

Predictive Models For Falls-Risk Assessment in Older People, Using Markerless Motion Capture

Falling in old age contributes to considerable misery for many people. Currently, there is a lack of practical, low cost and objective methods for identifying those at risk of falls. This thesis aims to address this need. The majority of the literature related to falls risk and balance impairment uses force plates to quantify postural sway. The use of such devices in a clinical setting is rare, mainly due to cost. However, some force-plate-based commercial products have been created, e.g. the Balance Master. To align the research in this thesis to both the literature and existing methods of assessing postural sway, a method is proposed which can generate sway metrics from the output of a low-cost markerless motion capture device (Kinect V2). Good agreement was found between the proposed method and the output of the Balance Master. A key reason for the lack of research into falls-risk using markerless motion capture, is the lack of an appropriate dataset. To address this issue, a dataset of clinical movements, recorded using markerless motion capture, was created. Named KINECAL, It contains the recordings of 90 participants, labelled by age and falls-risk. The data provided includes depth images, 3D joint positions, sway metrics and socioeconomic and health meta data. Many studies have noted that postural sway increases with age and conflate age-related changes with falls risk. However, if one examines sub-populations of older people, such as master athletes, It is clear that this is not necessarily true. The structure of KINECAL allows for the examination of age-related factors and falls-risk factors simultaneously. In addition, it includes labels of falls history, clinical impairment and comprehensive metadata. KINECAL was used to identify sway metrics most closely associated with falls risk, as distinct from the ageing process. Using the identified metrics, a model was developed that can identify those who would be classified as impaired by a range of clinical tests. Finally, a model is proposed, which can predict fallers by placing individuals on a scale of physical impairment. An autoencoder was used to model, healthy adult sit-to-stand movements. Using an anomaly detection approach, an individuals level of impairment can be plotted relative to this healthy standard. Using this model, the existence of two older populations (one with a high falls risk and one with a low falls risk) is demonstrated