The authors thank Dr. Honghua Zhou for digital technology support.&#160;This study was supported by Capital&#39;s Funds for Health Improvement and Research of China&#160;(ID:2024-2-7031).

This study was approved by the Academic Ethics Committee of the Seventh Medical Center of Chinese PLA General Hospital in Beijing, China.
1. Participant inclusion/exclusion criteria
<ol>
	<li>Recruit aged participants 65 years or older and obtain their informed consent.</li>
	<li>Exclude participants who have obvious visual and lower limb disability, such as knee arthritis, thromboangiitis obliterans, and gout.</li>
</ol>
2. Preparation of the test area
<ol>
	<li>Set up the standardized iTUG test area of 5 m x 8 m or wider (see Figure 1) with 12 cameras distributed around the room. Put the traditional TUG setups into the test area: a chair and a sign to remind the participant to turn back. 
	NOTE: Signs indicating route lines are optional.</li>
	<li>Ensure that the motion capture area is limited to the scope of all the cameras and all the TUG test setup is non-light reflective.</li>
</ol>
3. Software preparation for the procedures before the test
<ol>
	<li>Install the motion capture software on the computer to be used in the room.</li>
	<li>Click the Seeker button to start the motion capture software. After starting the software, for General Camara Configuration, choose the default mode (frame rate = 60 frames/s, shutter speed = 1/1,000 s), which is acceptable for most situations. Set Selected Camera Settings and Camera Configuration Settings also in the default mode.</li>
	<li>Select Live mode to set the real-time settings. 
	NOTE: Post mode is used to analyze the data captured.</li>
	<li>Click on Markersets to configure the marker settings.</li>
	<li>Select XY axis in the Calibration of Ground Axis and millimeters in Calibration units.</li>
	<li>Click on Calibrate to select the calibration variation.</li>
	<li>Select Initial Calibration and click on the &#34;L&#34; shaped button. At the same time, take the &#34;L&#34; shaped calibrator into the field and put it in the center of the field to make sure it can be captured by all the cameras. 
	NOTE: The &#34;L&#34; shaped calibrator contains four light-reflective markers.</li>
	<li>Check on the screen whether all the 12 cameras can detect four reflective markers. If any camera detects &#8804;3 markers, reduce lightness and threshold at the left of the screen. If any camera detects &#8805;5 markers, check the field and clean or cover the unwanted reflective markers. 
	NOTE: Some tiny belongings of the former participant might be detected by the camera.</li>
	<li>Remove the &#34;L&#34; shaped calibrator from the field.</li>
	<li>Click on the &#34;T&#34; shaped button. At the same time, take the &#34;T&#34; shaped calibrator into the field and wave it to make sure it can be captured by all the cameras.</li>
	<li>Select Z axis in the Calibration of Up Axis and millimeters in Calibration units.</li>
	<li>Have the doctors check whether all the cameras can capture the markers. Wave the markers in each corner of the field, especially covering the possible space of the TUG test.</li>
	<li>Check in the screen whether all 12 cameras can detect the &#34;T&#34; shaped calibrator. If any camera cannot detect it, change the direction of the camera. 
	NOTE: There are two shapes of markers that need to be calibrated; &#34;L&#34; shaped and &#34;T&#34; shaped. The &#34;L&#34; shaped calibrator has four light-reflective points to calibrate the XY axis, and the &#34;T&#34; shaped calibrator has four light-reflective points to calibrate the Z axis. The calibration duration will last 60 s or more. An effective capture will turn the color of the screen green.</li>
	<li>Click Finish to complete the calibration.</li>
	<li>Click Save Calibration to store the effective calibration mode. 
	NOTE: The calibration is performed in a 2D model; a 3D model is often used during the test.</li>
</ol>
4. iTUG test
NOTE: The participants should wear tight but comfortable clothes and shoes.
<ol>
	<li>Attach the reflective points on the anatomical landmarks: cervical 7 spinous process andthoracic 10 spinous process, left acromion and right acromion. 
	NOTE: Each participant could have up to 17 reflective points attached. The more reflective points that are attached, the more accurate the data collected, but also the less comfortable the participants feel.</li>
	<li>Right-click the reflective points at the right line of the screen and nominate them as C7, T10, left shoulder, and right shoulder.</li>
	<li>Show the instruction to the participants. The instruction is &#34;Please rise from the chair, walk 3 m at your preferred speed, turn around, return, and sit.&#34;</li>
	<li>Ask the participants to perform the iTUG test beforehand to make sure they are familiar with the instruction. 
	NOTE: Make sure each participant is comfortable after the reflective points are attached.</li>
	<li>Instruct the participant to perform the iTUG test. 
	NOTE: The participants need to walk to complete the iTUG task.</li>
	<li>While the participant is performing the iTUG test, click the start and stop buttons on the screen of the computer. 
	NOTE: During the iTUG test, the motion capture system samples data from all attached points at a frequency of 60 Hz; a video is formed accordingly (see Video 1).</li>
</ol>
5. Data collection and definition of iTUG test variables
<ol>
	<li>Click the Recording Setting button. 
	NOTE: The data are stored and found in a spreadsheet.</li>
	<li>Select Raw Camera Data |Tracked ASCTI | Tracked Binary. The Capture Duration is 20 s.</li>
	<li>Type in the name of the participant.</li>
	<li>Click the Record button to start data collection.</li>
	<li>Identify sub-phases of the iTUG test by reviewing the video and calculate the variables according to the data.
	<ol>
		<li>Define the following variables: traditional TUG test total time, phase 1 time (rising from the chair), phase 1 body sway (rising from the chair), phase 2 time (walking 3 m at the preferred speed), phase 2 body sway (walking 3 m at the preferred speed), phase 3 time (turning around), phase 3 body sway (turning around), angular velocity of phase 3 (turning around), phase 4 time (returning), phase 4 body sway (returning), and phase 5 time (sitting). 
		NOTE: The details are similar to those described by Caronni and colleagues15.</li>
	</ol>
	</li>
</ol>
6. Downton Fall Risk Index (DFRI)
<ol>
	<li>Assess the falling risk using the Downton Fall Risk Index (DFRI). 
	NOTE: The DFRI (Table 1) includes 11 risk items, which are scored one point each. Scores are summed to a total index score, range 0-11. A score of &#8805;3 is considered to indicate a high risk of falls. To evaluate falling risk, DFRI is usually used for participants admitted in a hospital, and the Home Falls and Accidents Screening Tool (HOME FAST) is more suitable for community dwellers.</li>
</ol>
7. Statistical analysis
<ol>
	<li>Use a commercially available statistical software package to perform all statistical analyses. Use Student&#39;s t-test to assess group differences and choose Pearson correlation coefficient to assess the relationship between subcomponents of iTUG and DFRI score on the total sample, with P &#60; 0.05 indicating a statistically significant difference.</li>
	<li>Use the Bland-Altman procedures to assess agreement for Phase 1 duration, Phase 3 angular velocity, and Phase 4 duration between our method and the McRoberts sensor (see the Table of Materials). Calculate the mean difference between the two methods of measurement and the 95% limit of agreement for the mean difference calculated.</li>
</ol>

Evaluating the Risk of Falling in Elderly Using iTUG Motion Capture Technology

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R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effects+of+total+ankle+replacement+on+ankle+joint+mechanics+during+walking.">The effects of total ankle replacement on ankle joint mechanics during walking.</a> J Sport Health Sci. 6 (3), 340-345 (2017).</li><li>Mehdizadeh, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Toronto+older+adults+gait+archive:+video+and+3D+inertial+motion+capture+data+of+older+adults'+walking.">The Toronto older adults gait archive: video and 3D inertial motion capture data of older adults' walking.</a> Sci Data. 9 (1), 398 (2022).</li><li>Caronni, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Criterion+validity+of+the+instrumented+Timed+Up+and+Go+test:+A+partial+least+square+regression+study.">Criterion validity of the instrumented Timed Up and Go test: A partial least square regression study.</a> Gait Posture. 61, 287-293 (2018).</li><li>Mojtaba, M., Alinaghizadeh, H., Rydwik, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Downton+Fall+Risk+Index+during+hospitalisation+is+associated+with+fall-related+injuries+after+discharge:+a+longitudinal+observational+study.">Downton Fall Risk Index during hospitalisation is associated with fall-related injuries after discharge: a longitudinal observational study.</a> J Physiother. 64 (3), 172-177 (2018).</li><li>Hershkovitz, L., Malcay, O., Grinberg, Y., Berkowitz, S., Kalron, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+contribution+of+the+instrumented+Timed-Up-and-Go+test+to+detect+falls+and+fear+of+falling+in+people+with+multiple+sclerosis.">The contribution of the instrumented Timed-Up-and-Go test to detect falls and fear of falling in people with multiple sclerosis.</a> Mult Scler Relat Disord. 27, 226-231 (2019).</li><li>Zarzeczny, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Aging+effect+on+the+instrumented+Timed-Up-and-Go+test+variables+in+nursing+home+women+aged+80-93+years.">Aging effect on the instrumented Timed-Up-and-Go test variables in nursing home women aged 80-93 years.</a> Biogerontology. 18 (4), 651-663 (2017).</li><li>Kim, K. 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The authors have no conflicts of interest to disclose.

The critical steps in the protocol are to attach the reflective points accurately to the anatomical landmarks to avoid bias. Furthermore, the identification of each subcomponent of the iTUG test is also a critical step; a video review is helpful for the identification.
A marginal difference existed between groups in the TUG test scores implying that traditional TUG scores might not be sensitive enough to discriminate risk of falling. We did not find obvious differences between the groups in Ph...

Falling is one of the most common geriatric syndromes and is the second leading cause of accidental or unintentional injury-related deaths worldwide1. In adults aged above 65 years, falling can result in functional impairment, disability, decreased quality of life, increased length of stay in hospitals, and even mortality2,3. Therefore, preventing falls is of utmost importance.
To determine predictors of fall events, previous researchers have focused on gait analyses, balance tests, mental state, sedative drug use, as well as history of falling in the preceding year4,5 The Timed Up and Go (TUG) test is a quick performance-based measure of mobility. The TUG test has been extensively studied in older adults and is recommended as a simple screening test for the risk of falls6. This widely used test consists of rising from a chair, walking 3 m at the preferred speed, turning around, returning, and sitting. The traditional clinical outcome of this test depends on its total duration7 and is assessed by a stopwatch.
In clinical practice, the conventional TUG test measures the total time to perform a series of activities without dividing the performance of the subject into subcomponents8. Recently, some investigators have proposed that different TUG test components might be particularly sensitive as predictors of future falls9. When using the digitized instrumented TUG (iTUG) test, the individual components of the TUG test can be analyzed separately. By using the iTUG, it is possible to objectively evaluate several characteristics of each TUG test sub-phase and obtain quantitative data, such as the relevant durations, velocities, and angular velocity of each movement. With more detailed data, the iTUG test has shown the advantage of detecting specific deficits that may be more indicative of the fall risk10.
As the gold standard in movement analysis, motion capture technologies have been used to detect movement in patients with Parkinson&#39;s Disease (PD)11, cognitive impairment12, and ankle arthritis13, as well as in healthy adults14. In the current study, we aimed to analyze the iTUG test subcomponents using motion capture technology and to determine the correlation between iTUG test subtasks and the potential risk of future falls.

<table><tbody><tr><td>Black strip</td><td>Deli</td><td>60 mm x 20 m</td><td></td></tr><tr><td>Calibrator</td><td>NOKOV</td><td>reflector marker1</td><td>L shape</td></tr><tr><td>Calibrator</td><td>NOKOV</td><td>reflector marker2</td><td>T shape</td></tr><tr><td>Chair</td><td>YUANSHENGYUANDAI</td><td>&amp;ldquo;10076062317820&amp;rdquo;</td><td></td></tr><tr><td>Computer</td><td>HUAWEI</td><td>HONOR</td><td></td></tr><tr><td>McRoberts sensor&amp;nbsp;</td><td>DynaPort Hybrid, McRoberts, The Hague, The Netherland</td><td></td><td></td></tr><tr><td>Motion capture camera</td><td>NOKOV</td><td>Mars2H</td><td></td></tr><tr><td>Motion capture software</td><td>NOKOV</td><td>DG-01</td><td></td></tr><tr><td>Reflective marker</td><td>NOKOV</td><td>small marker</td><td>for calibrators</td></tr><tr><td>Reflective marker</td><td>NOKOV</td><td>large marker</td><td>for participants</td></tr></tbody></table>

using motion capture technology in the instrumented timed up and go test to detect the risk of falling in aged adults

Despite efforts made by medicine and technology, the incidence of falls in older adults is still increasing. Therefore, early detection of the falling risk is becoming increasingly important for falling prevention. The Timed Up and Go (TUG) test is a well-accepted tool to assess mobility and can be used in predicting future fall risk in aged adults. In clinical practice, the total time to complete the test is the main outcome measure of the TUG test. Owing to its simplicity and generality, the traditional TUG test has been considered a global test for movement analysis. However, recently, researchers have attempted to split the TUG test into subcomponents and have updated its score system for further investigations. The instrumented Time Up and Go (iTUG) test, which is a new modification of the traditional TUG test, has been reported to be a sensitive tool for predicting movement disorders and the risk of falls in older adults. The goal of the present study was to analyze the iTUG test subcomponents using motion capture technology, and to determine which iTUG test subtasks are related to the potential risk of future falls.

Thirteen aged participants with a high risk of falling (DFRI score: 3-11) and 11 aged subjects with a low risk of falling (DFRI score: 0-2) were recruited. The DFRI is detailed in Table 1. As has been mentioned previously, a score of 3 or more is considered to indicate a high risk of falls for patients during hospitalization16.
Demographic data are shown in Table 1, which...

Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights

The instrumented Timed Up and Go (iTUG) test is gaining increasing attention in body sway and gait analysis with the development of new technologies. We present a protocol to analyze the subcomponents of the iTUG with motion capture.

Using Motion Capture Technology in the Instrumented Timed Up and Go Test to Detect the Risk of Falling in Aged Adults

Despite efforts made by medicine and technology, the incidence of falls in older adults is still increasing. Therefore, early detection of the falling ...

using-motion-capture-technology-instrumented-timed-up-go-test-to

Research

JoVE Journal

Medicine

768 Views.  The Seventh Medical Center of Chinese PLA General Hospital. The instrumented Timed Up and Go (iTUG) test is gaining increasing attention in body sway and gait analysis with the development of new technologies. We present a protocol to analyze the subcomponents of the iTUG with motion capture.

Video: Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights

Community-based Adapted Tango Dancing for Individuals with Parkinson's Disease and Older Adults

Adapted tango dancing improves mobility and balance in older adults and additional populations with balance impairments. It is composed of very simple step elements. Adapted tango involves movement initiation and cessation, multi-directional perturbations, varied speeds and rhythms. Focus on foot placement, whole body coordination, and attention to partner, path of movement, and aesthetics likely underlie adapted tango&#8217;s demonstrated efficacy for improving mobility and balance. In this paper, we describe the methodology to disseminate the adapted tango teaching methods to dance instructor trainees and to implement the adapted tango by the trainees in the community for older adults and individuals with Parkinson&#8217;s Disease (PD). Efficacy in improving mobility (measured with the Timed Up and Go, Tandem stance, Berg Balance Scale, Gait Speed and 30 sec chair stand), safety and fidelity of the program is maximized through targeted instructor and volunteer training and a structured detailed syllabus outlining class practices and progression.

Adapted tango has demonstrated efficacy for improving mobility and balance. We describe the dissemination of adapted tango teaching methods to dance instructor trainees and the implementation of adapted tango by the trainees in the community for improving mobility and balance in older adults and individuals with Parkinson&#8217;s disease.

Adapted tango dancing improves mobility and balance in older adults and additional populations with balance impairments. It is composed of very simple ...

Behavior

Substantiating Appropriate Motion Capture Techniques for the Assessment of Nordic Walking Gait and Posture in Older Adults

Nordic walking (NW) has become a safe and simple form of exercise in recent years, and in studying this gait pattern, various data collection techniques have been employed, each with positives and negatives. The aim was to determine the effect of NW on older adult gait and posture and to determine optimal use of different data collection systems in both short and long duration analysis. Gait and posture during NW and normal walking were assessed in 17 healthy older adults (age: 69 &#177; 7.3). Participants performed two trials of 6 Minute Walk Tests (6MWT) (1 with poles (WP) and 1 without poles (NP)) and 6 trials of a 5m walk (3 WP and 3 NP). Motion was recorded using two systems, a 6-sensor accelerometry system and an 8-camera 3-dimensional motion capture system, in order to quantify spatial-temporal, kinematic, and kinetic parameters.
With both systems, participants demonstrated increased stride length and double support and decreased gait speed and cadence WP compared to NP (p &#60;0.05). Also, with motion capture, larger single support time was found WP (p &#60;0.05). With 3-D capture, smaller hip power generation and moments of force were found at heel contact and pre-swing as well as smaller knee power absorption at heel contact, pre-swing, and terminal swing WP compared to NP, when assessed over one cycle (p &#60;0.05). Also, WP yielded smaller moments of force at heel contact and terminal swing along with larger moments at mid-stance of a gait cycle (p &#60;0.05). No changes were found for posture.
NW seems appropriate for promoting a normal gait pattern in older adults. Three-dimensional motion capture should primarily be used during short duration gait analysis (i.e. single gait cycle), while accelerometry systems should be primarily employed in instances requiring longer duration analysis such as during the 6MWT.

The aim was to substantiate optimal use of data collection techniques for Nordic walking gait and posture analysis. Three-dimensional motion capture should be used during short duration analysis (i.e. single gait cycle), while accelerometry should be employed for longer duration analysis (i.e. repeated cycles) like a 6 Minute Walk Test.

Nordic walking (NW) has become a safe and simple form of exercise in recent years, and in studying this gait pattern, various data collection techniques ...

Measuring the Kinematics of Daily Living Movements with Motion Capture Systems in Virtual Reality

The inability to complete instrumental activities of daily living (IADL) is a precursor to various neuropsychological diseases. Questionnaire-based assessments of IADL are easy to use but prone to subjective bias. Here, we describe a novel virtual reality (VR) test to assess two complex IADL tasks: handling financial transactions and using public transportation. While a participant performs the tasks in a VR setting, a motion capture system traces the position and orientation of the dominant hand and head in a three-dimensional Cartesian coordinate system. Kinematic raw data are collected and converted into &#39;kinematic performance measures,&#39; i.e., motion trajectory, moving distance, and time to completion. Motion trajectory is the path of a particular body part (e.g., dominant hand or head) in space. Moving distance refers to the total distance of the trajectory, and time to completion is how long it took to complete an IADL task. These kinematic measures could discriminate patients with cognitive impairment from healthy controls. The development of this kinematic measuring protocol allows detection of early IADL-related cognitive impairments.

We designed a virtual reality test to assess instrumental activities of daily living (IADL) with a motion capture system. We propose a detailed kinematic analysis to interpret the participant&#39;s various movements, including trajectory, moving distance, and time to completion to evaluate IADL capabilities.

The inability to complete instrumental activities of daily living (IADL) is a precursor to various neuropsychological diseases. Questionnaire-based ...

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

A real-time locating system (RTLS) can be used to track the walking activity of institutionalized older adults in long-term care who are at risk for wandering behaviors. The benefits of a RTLS are objective and continuous measurements of activity. Self-report methods of activity, especially wandering, by health care staff are vulnerable to floor effects and recall bias, and continuous clinical or research observation over the long-term can be time-consuming and expensive. Health care staff also fail to recognize the onset and/or duration of wandering behaviors, which are associated with a variety of adverse health outcomes in this population but amenable to intervention. RTLS technologies can measure the walking activity of institutionalized residents with cognitive impairment over time with a high degree of accuracy. This is particularly useful for the study of wandering, defined as walking for at least 60 seconds with few (if any) breaks in activity. Wandering is associated with disease progression, hospitalizations, falls and death. Previous work suggests older adults with poor balance ability and high sustained walking activity may be particularly susceptible to poor health outcomes. RTLS&#39;s are used to assess cognitive impairment and factors associated with gait and balance; however, supplemental paper and pencil gait/balance tools may be used to further refine risk profiles. This project discusses the use of a RTLS to measure walking activity and also gait quality and balance ability measures on this population.

This paper discusses the use of a continuous and objective real-time locating system to measure walking activity associated with wandering behaviors, focusing on older adults with cognitive impairment. Walking activity is measured by walking distance, sustained walking distance, and sustained gait speed. Also assessed are gait quality and balance ability.

A real-time locating system (RTLS) can be used to track the walking activity of institutionalized older adults in long-term care who are at risk for ...

An Instrumented Pull Test to Characterize Postural Responses

Impairment of postural reflexes, termed postural instability, is a common and disabling deficit in Parkinson's disease. To assess postural reflexes, clinicians typically employ the pull test to grade corrective responses to a backward perturbation at the shoulders. However, the pull test is prone to issues with reliability and scaling (score/4). Here, we present an instrumented version of the pull test to more precisely quantify postural responses. Akin to the clinical test, pulls are manually administered except pull force is also recorded. Displacements of the trunk and feet are captured by a semi-portable motion tracking system. Raw data represent distance traveled (in millimeter units), making subsequent interpretation and analysis intuitive. The instrumented pull test also detects variabilities influencing pull test administration, such as pull force, thereby identifying and quantifying potential confounds that can be accounted for by statistical techniques. The instrumented pull test could have application in studies seeking to capture early abnormalities in postural responses, track postural instability over time, and detect responses to therapy.

Impairment of postural reflexes, termed postural instability, is difficult to quantify. Clinical assessments such as the pull test suffer issues with reliability and scaling. Here, we present an instrumented version of the pull test to objectively characterize postural responses.

Impairment of postural reflexes, termed postural instability, is a common and disabling deficit in Parkinson's disease. To assess postural reflexes, ...

Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication

Computerized dynamic posturography with the EquiTest is an objective technique for measuring postural strategies under challenging static and dynamic conditions. As part of a diagnostic assessment, the early detection of postural deficits is important so that appropriate and targeted interventions can be prescribed. The Sensory Organization Test (SOT) on the EquiTest determines an individual&#39;s use of the sensory systems (somatosensory, visual, and vestibular) that are responsible for postural control. Somatosensory and visual input are altered by the calibrated sway-referenced support surface and visual surround, which move in the anterior-posterior direction in response to the individual&#39;s postural sway. This creates a conflicting sensory experience. The Motor Control Test (MCT) challenges postural control by creating unexpected postural disturbances in the form of backwards and forwards translations. The translations are graded in magnitude and the time to recover from the perturbation is computed.
Intermittent claudication, the most common symptom of peripheral arterial disease, is characterized by a cramping pain in the lower limbs and caused by muscle ischemia secondary to reduced blood flow to working muscles during physical exertion. Claudicants often display poor balance, making them susceptible to falls and activity avoidance. The Ankle Brachial Pressure Index (ABPI) is a noninvasive method for indicating the presence of peripheral arterial disease and intermittent claudication, a common symptom in the lower extremities. ABPI is measured as the highest systolic pressure from either the dorsalis pedis or posterior tibial artery divided by the highest brachial artery systolic pressure from either arm. This paper will focus on the use of computerized dynamic posturography in the assessment of balance in claudicants.

Individuals with intermittent claudication exhibit poor balance compared to healthy controls. Computerized dynamic posturography is an objective method for measuring an individual's postural responses to balance disturbances. This provides an objective reflection of the person&#x2019;s ability to respond to situations under which sensory stimuli are altered and unexpected perturbations occur.

Computerized dynamic posturography with the EquiTest is an objective technique for measuring postural strategies under challenging static and dynamic ...

Quantitative Static and Dynamic Assessment of Balance Control in Stroke Patients

In patients with stroke, damage to the central nervous system (CNS) can affect the postural stability and increase the risk of falling. Therefore, accurately assessing the balance is important to understand the type, extent, and causes of balance deficit, and to identify individualized interventions. Clinical assessment methods for balance function can be broadly divided into observation, scale assessment, and balance instrument testing. Here, a clinical protocol is presented for static and dynamic balance assessment in stroke patients, which includes three semiquantitative balance function scale assessments (i.e., Berg Balance Scale, Timed Up and Go Test, and Fugl-Meyer Assessment) and three quantitative instrumental balance evaluation (i.e., Stability Assessment Module, Proprioceptive Assessment Module, and Limit of Stability Module). It is recommended that clinicians consider the use of both classic clinical balance scales and instrumental balance measurements when assessing stroke patients to improve the accuracy of assessments, leading to a better individualized treatment plan.

Presented here is a quantitative, clinical balance assessment method suitable for stroke patients with balance disorders.

In patients with stroke, damage to the central nervous system (CNS) can affect the postural stability and increase the risk of falling. Therefore, ...

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults

Spatial and temporal characteristics of human walking are frequently evaluated to identify possible gait impairments, mainly in orthopedic and neurological patients1-4, but also in healthy older adults5,6. The quantitative gait analysis described in this protocol is performed with a recently-introduced photoelectric system (see&#160;Materials table) which has the potential to be used in the clinic because it is portable, easy to set up (no subject preparation is required before a test), and does not require maintenance and sensor calibration. The photoelectric system consists of series of high-density floor-based photoelectric cells with light-emitting and light-receiving diodes that are placed parallel to each other to create a corridor, and are oriented perpendicular to the line of progression7. The system simply detects interruptions in light signal, for instance due to the presence of feet within the recording area. Temporal gait parameters and 1D spatial coordinates of consecutive steps are subsequently calculated to provide common gait parameters such as step length, single limb support and walking velocity8, whose validity against a criterion instrument has recently been demonstrated7,9. The measurement procedures are very straightforward; a single patient can be tested in less than 5 min&#160;and a comprehensive report can be generated in less than 1&#160;min.

This protocol is used to evaluate spatial and temporal gait variables of neurological/orthopedic patients and older persons by means of a recently-introduced floor-based photocell system.

Spatial and temporal characteristics of human walking are frequently evaluated to identify possible gait impairments, mainly in orthopedic and ...

Exergaming in Older People Living with HIV Improves Balance, Mobility and Ameliorates Some Aspects of Frailty

Approximately 1.2 million people in the United States live with HIV infection. Medical advancements have increased the life expectancy and this cohort is aging. HIV-positive individuals have a high incidence of frailty (~20%) characterized by depression and sedentary behavior. Exercise would be healthy, but due to the frail status of many HIV-positive individuals, conventional exercise is too taxing. The aim of this study was to evaluate the effectiveness and acceptability of a novel game-based training program (exergame) in ameliorating some aspects of frailty in HIV-infected individuals. Ten older people living with HIV were enrolled in an exergame intervention. Patients performed balance exercises such as weight shifting, ankle reaching, and obstacle crossing. Real-time visual/audio lower-extremity joint motion feedback was provided using wearable sensors to assist feedback and encourage subjects to accurately execute each exercise task. Patients trained twice a week for 45 min for 6 weeks. Changes in balance, gait, psychosocial parameters and quality of life parameters were assessed at the beginning, midterm and at conclusion of the training program. Ten patients completed the study and their results analyzed. The mean age was 57.2 &#177; 9.2 years. The participants showed a significant reduction in center of mass sway (78.2%, p = .045) during the semi-tandem balance stance with eyes closed and showed a significant increase in gait speed during a dual task motor-cognitive assessment (9.3%, p = .048) with an increase in stride velocity of over 0.1 m/sec. A significant reduction in reported pain occurred (43.5%, p = .041). Preliminary results of this exergame intervention show promise in improving balance and mobility while requiring older people living with HIV to be more active. The exergame can be continued at home and may have long term as well as short-term benefits for ameliorating frailty associated with HIV infection.

Persons infected with HIV are often frail, depressed and live a sedentary lifestyle for which conventional exercise is too taxing. Here, we present an exercise protocol that ameliorates aspects of frailty in HIV-infected persons. An exergame integrating cognitive control was developed using biosensors that measured balance, weight-shifting and obstacle crossing.

Approximately 1.2 million people in the United States live with HIV infection. Medical advancements have increased the life expectancy and this cohort is ...

Design and Analysis for Fall Detection System Simplification

This paper presents a methodology based on multimodal sensors to configure a simple, comfortable and fast fall detection and human activity recognition system that can be easily implemented and adopted. The methodology is based on the configuration of specific types of sensors, machine-learning methods and procedures. The protocol is divided into four phases: (1) database creation (2) data analysis (3) system simplification and (4) evaluation. Using this methodology, we created a multimodal database for fall detection and human activity recognition, namely UP-Fall Detection. It comprises data samples from 17 subjects that perform 5 types of falls and 6 different simple activities, during 3 trials. All information was gathered using 5 wearable sensors (tri-axis accelerometer, gyroscope and light intensity), 1 electroencephalograph helmet, 6 infrared sensors as ambient sensors, and 2 cameras in lateral and front viewpoints. The proposed novel methodology adds some important stages to perform a deep analysis of the following design issues in order to simplify a fall detection system: a) select which sensors or combination of sensors are to be used in a simple fall detection system, b) determine the best placement of the sources of information, and c) select the most suitable machine learning classification method for fall and human activity detection and recognition. Even though some multimodal approaches reported in literature only focus on one or two of the above-mentioned issues, our methodology allows simultaneously solving these three design problems related to a human fall and activity detection and recognition system.

We present a methodology based on multimodal sensors to configure a simple, comfortable and fast fall detection and human activity recognition system. The goal is to build a system for accurate fall detection that can be easily implemented and adopted.

This paper presents a methodology based on multimodal sensors to configure a simple, comfortable and fast fall detection and human activity recognition ...