Digital Measures of Postural Sway Quantify Balance Deficits in Spinocerebellar Ataxia

BACKGROUND

Maintaining balance is crucial for independence and quality of life. Loss of balance is a hallmark of spinocerebellar ataxia (SCA).

OBJECTIVE

The aim of this study was to identify which standing balance conditions and digital measures of body sway were most discriminative, reliable, and valid for quantifying balance in SCA.

METHODS

Fifty-three people with SCA (13 SCA1, 13 SCA2, 14 SCA3, and 13 SCA6) and Scale for Assessment and Rating of Ataxia (SARA) scores 9.28 ± 4.36 and 31 healthy controls were recruited. Subjects stood in six test conditions (natural stance, feet together and tandem, each with eyes open [EO] and eyes closed [EC]) with an inertial sensor on their lower back for 30 seconds (×2). We compared test completion rate, test-retest reliability, and areas under the receiver operating characteristic curve (AUC) for seven digital sway measures. Pearson's correlations related sway with the SARA and the Patient-Reported Outcome Measure of Ataxia (PROM ataxia).

RESULTS

Most individuals with SCA (85%-100%) could stand for 30 seconds with natural stance EO or EC, and with feet together EO. The most discriminative digital sway measures (path length, range, area, and root mean square) from the two most reliable and discriminative conditions (natural stance EC and feet together EO) showed intraclass correlation coefficients from 0.70 to 0.91 and AUCs from 0.83 to 0.93. Correlations of sway with SARA were significant (maximum r = 0.65 and 0.73). Correlations with PROM ataxia were mild to moderate (maximum r = 0.56 and 0.34).

CONCLUSION

Inertial sensor measures of extent of postural sway in conditions of natural stance EC and feet together stance EO were discriminative, reliable, and valid for monitoring SCA. © 2024 International Parkinson and Movement Disorder Society.

Standing Balance Conditions and Digital Sway Measures for Clinical Trials of Friedreich's Ataxia

BACKGROUND

Progressive loss of standing balance is a feature of Friedreich's ataxia (FRDA).

OBJECTIVES

This study aimed to identify standing balance conditions and digital postural sway measures that best discriminate between FRDA and healthy controls (HC). We assessed test-retest reliability and correlations between sway measures and clinical scores.

METHODS

Twenty-eight subjects with FRDA and 20 HC completed six standing conditions: feet apart, feet together, and feet tandem, both with eyes opened (EO) and eyes closed. Sway was measured using a wearable sensor on the lumbar spine for 30 seconds. Test completion rate, test-retest reliability with intraclass correlation coefficients, and areas under the receiver operating characteristic curves (AUCs) for each measure were compared to identify distinguishable FRDA sway characteristics from HC. Pearson correlations were used to evaluate the relationships between discriminative measures and clinical scores.

RESULTS

Three of the six standing conditions had completion rates over 70%. Of these three conditions, natural stance and feet together with EO showed the greatest completion rates. All six of the sway measures' mean values were significantly different between FRDA and HC. Four of these six measures discriminated between groups with >0.9 AUC in all three conditions. The Friedreich Ataxia Rating Scale Upright Stability and Total scores correlated with sway measures with P-values <0.05 and r-values (0.63-0.86) and (0.65-0.81), respectively.

CONCLUSION

Digital postural sway measures using wearable sensors are discriminative and reliable for assessing standing balance in individuals with FRDA. Natural stance and feet together stance with EO conditions suggest use in clinical trials for FRDA. © 2024 International Parkinson and Movement Disorder Society.

Assessment of Mobility Trajectories Using Wearable Inertial Sensors During Autologous Hematopoietic Cell Transplant

OBJECTIVE

This study aimed to characterize mobility patterns using wearable inertial sensors and serial assessment across autologous hematopoietic cell transplant (autoHCT) and investigate the relation between mobility and perceived function in patients with hematologic cancer.

DESIGN

Prospective longitudinal study.

SETTING

Hospital adult transplant clinic followed by discharge.

PARTICIPANTS

78 patients with hematological cancer receiving autoHCT.

MAIN OUTCOME MEASURES

Mobility was measured across 3 clinical phases (pretransplant, pre-engraftment, and post-engraftment) in using inertial sensors worn during prescribed performance tests in the hospital. Perceived function was assessed using validated provider-reported (Eastern Cooperative Oncology Group [ECOG] Performance Status Scale) and patient-reported [European Organization for Research and Treatment of Cancer Quality of Life Questionnaire [EORTC QLQ-C30]) measures. Trajectories of 5 selected mobility characteristics (turn duration, gait speed, stride time variability, double support time, and heel strike angle) across the clinical phases were also evaluated using piecewise linear mixed-effects models.

RESULTS

Using Principal Components Analysis, 4 mobility patterns were identified pretransplant: Gait Limitation, Sagittal Sway, Coronal Sway, and Balance Control. Gait Limitation measured pretransplant was significantly inversely associated with perceived function reported by the provider- (β = -0.11; 95% CI: -0.19, -0.02) and patient- (β = -4.85; 95% CI: -7.72, -1.99) post-engraftment in age-adjusted linear regression models. Mobility characteristics demonstrated immediate declines early pre-engraftment with stabilization by late pre-engraftment.

CONCLUSION

Patients with hematological cancer experiencing gait limitations pretransplant are likely to have worse perceived function post-engraftment. Mobility declines in early phases post-transplant and may not fully recover, indicating an opportunity for timely rehabilitation referrals. Wearable inertial sensors can be used to identify early mobility problems and patients who may be at risk for future functional decline who may be candidates for early physical rehabilitation.

Mobility Rehab visual feedback system for gait rehabilitation in older adults

BACKGROUND

Gait and balance impairments are among the main causes of falls in older adults. The feasibility and effectiveness of adding sensor-based feedback to physical therapy (PT) in an outpatient PT setting is unknown. We evaluated the feasibility and effectiveness of PT intervention combined with a therapist-assisted visual feedback system, called Mobility Rehab, (PT + MR) in older adults.

METHODS

Twenty-eight older adults with and without neurological diseases were assigned either PT + MR (n = 22) or PT alone (n = 6). Both groups performed 8 sessions (individualized) of 45 min long (30 min for gait training and 15 min for endurance, strength, and balance exercises) in an outpatient clinic. Mobility Rehab uses unobtrusive, inertial sensors on both wrists and feet, and at the sternum level with real-time algorithms to provide real-time feedback on five gait metrics (step duration, stride length, elevation at mid-swing, arm swing range-of-motion [ROM], and trunk coronal ROM), which are displayed on a tablet. The primary outcome was the Activities-specific Balance Confidence scale (ABC). The secondary outcome was gait speed measured with wearable inertial sensors during 2 min of walking.

RESULTS

There were no between-group differences at baseline for any variable (P > 0.05). Neither PT + MR nor PT alone showed significant changes on the ABC scores. PT + MR, but not PT alone, showed significant improvements in gait speed and arm swing ROM. The system was evaluated as 'easy to use' by the PT.

CONCLUSIONS

Our preliminary results show that PT + MR improves gait speed in older adults with and without neurological diseases in an outpatient clinic.

CLINICAL TRIAL REGISTRATION

www.

CLINICALTRIALS

gov , identifier: NCT03869879.

Gait and turning characteristics from daily life increase ability to predict future falls in people with Parkinson's disease

Objectives

To investigate if digital measures of gait (walking and turning) collected passively over a week of daily activities in people with Parkinson's disease (PD) increases the discriminative ability to predict future falls compared to fall history alone.

Methods

We recruited 34 individuals with PD (17 with history of falls and 17 non-fallers), age: 68 ± 6 years, MDS-UPDRS III ON: 31 ± 9. Participants were classified as fallers (at least one fall) or non-fallers based on self-reported falls in past 6 months. Eighty digital measures of gait were derived from 3 inertial sensors (Opal® V2 System) placed on the feet and lower back for a week of passive gait monitoring. Logistic regression employing a "best subsets selection strategy" was used to find combinations of measures that discriminated future fallers from non-fallers, and the Area Under Curve (AUC). Participants were followed via email every 2 weeks over the year after the study for self-reported falls.

Results

Twenty-five subjects reported falls in the follow-up year. Quantity of gait and turning measures (e.g., number of gait bouts and turns per hour) were similar in future fallers and non-fallers. The AUC to discriminate future fallers from non-fallers using fall history alone was 0.77 (95% CI: [0.50-1.00]). In contrast, the highest AUC for gait and turning digital measures with 4 combinations was 0.94 [0.84-1.00]. From the top 10 models (all AUCs>0.90) via the best subsets strategy, the most consistently selected measures were variability of toe-out angle of the foot (9 out of 10), pitch angle of the foot during mid-swing (8 out of 10), and peak turn velocity (7 out of 10).

Conclusions

These findings highlight the importance of considering precise digital measures, captured via sensors strategically placed on the feet and low back, to quantify several different aspects of gait (walking and turning) during daily life to improve the classification of future fallers in PD.

Opal Actigraphy (Activity and Sleep) Measures Compared to ActiGraph: A Validation Study

Physical activity and sleep monitoring in daily life provide vital information to track health status and physical fitness. The aim of this study was to establish concurrent validity for the new Opal Actigraphy solution in relation to the widely used ActiGraph GT9X for measuring physical activity from accelerometry epic counts (sedentary to vigorous levels) and sleep periods in daily life. Twenty participants (age 56 + 22 years) wore two wearable devices on each wrist for 7 days and nights, recording 3-D accelerations at 30 Hz. Bland-Altman plots and intraclass correlation coefficients (ICCs) assessed validity (agreement) and test-retest reliability between ActiGraph and Opal Actigraphy sleep durations and activity levels, as well as between the two different versions of the ActiGraph. ICCs showed excellent reliability for physical activity measures and moderate-to-excellent reliability for sleep measures between Opal versus Actigraph GT9X and between GT3X versus GT9X. Bland-Altman plots and mean absolute percentage error (MAPE) also show a comparable performance (within 10%) between Opal and ActiGraph and between the two ActiGraph monitors across activity and sleep measures. In conclusion, physical activity and sleep measures using Opal Actigraphy demonstrate performance comparable to that of ActiGraph, supporting concurrent validation. Opal Actigraphy can be used to quantify activity and monitor sleep patterns in research and clinical studies.

Feasibility of a Novel Therapist-Assisted Feedback System for Gait Training in Parkinson's Disease

We tested the feasibility of one session of treadmill training using a novel physical therapist assisted system (Mobility Rehab) using wearable sensors on the upper and lower limbs of 10 people with Parkinson's disease (PD). Participants performed a 2-min walk overground before and after 15 min of treadmill training with Mobility Rehab, which included an electronic tablet (to visualize gait metrics) and five Opal sensors placed on both the wrists and feet and on the sternum area to measure gait and provide feedback on six gait metrics (foot-strike angle, trunk coronal range-of-motion (ROM), arm swing ROM, double-support duration, gait-cycle duration, and step asymmetry). The physical therapist used Mobility Rehab to select one or two gait metrics (from the six) to focus on during the treadmill training. Foot-strike angle (effect size (ES) = 0.56, 95% Confidence Interval (CI) = 0.14 to 0.97), trunk coronal RoM (ES = 1.39, 95% CI = 0.73 to 2.06), and arm swing RoM (ES = 1.64, 95% CI = 0.71 to 2.58) during overground walking showed significant and moderate-to-large ES following treadmill training with Mobility Rehab. Participants perceived moderate (60%) and excellent (30%) effects of Mobility Rehab on their gait. No adverse events were reported. One session of treadmill training with Mobility Rehab is feasible for people with mild-to-moderate PD.

Using Wearable Inertial Sensors to Assess Mobility of Patients With Hematologic Cancer and Associations With Chemotherapy-Related Symptoms Before Autologous Hematopoietic Stem Cell Transplant: Cross-sectional Study

BACKGROUND

Wearable sensors could be a simple way to quantify and characterize mobility in patients with hematologic cancer scheduled to receive autologous hematopoietic stem cell transplant (autoHSCT) and how they may be related to common treatment-related symptoms and side effects of induction chemotherapy.

OBJECTIVE

We aimed to conduct a cross-sectional study comparing mobility in patients scheduled to receive autoHSCT with that in healthy, age-matched adult controls and determine the relationships between patient mobility and chemotherapy-related symptoms.

METHODS

Patients scheduled to receive autoHSCT (78/156, 50%) and controls (78/156, 50%) completed the prescribed performance tests using wearable inertial sensors to quantify mobility including turning (turn duration and number of steps), gait (gait speed, stride time, stride time variability, double support time, coronal trunk range of motion, heel strike angle, and distance traveled), and balance (coronal sway, coronal range, coronal velocity, coronal centroidal frequency, sagittal sway, sagittal range, sagittal velocity, and sagittal centroidal frequency). Patients completed the validated patient-reported questionnaires to assess symptoms common to chemotherapy: chemotherapy-induced peripheral neuropathy (Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity subscale), nausea and pain (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire), fatigue (Patient-Reported Outcomes Measurement Information System Fatigue Short Form 8a), vertigo (Vertigo Symptom Scale-short form), and depression (Center for Epidemiological Studies-Depression). Paired, 2-sided t tests were used to compare mobility between patients and controls. Stepwise multivariable linear regression models were used to evaluate associations between patient mobility and symptoms.

RESULTS

Patients aged 60.3 (SD 10.3) years had significantly worse turning (turn duration; P<.001), gait (gait speed, stride time, stride time variability, double support time, heel strike angle, stride length, and distance traveled; all P<.001), and balance (coronal sway; P<.001, range; P<.001, velocity; P=.02, and frequency; P=.02; and sagittal range; P=.008) than controls. In patients, high nausea was associated with worse stride time variability (ß=.001; P=.005) and heel strike angle (ß=-.088; P=.02). Pain was associated with worse gait speed (ß=-.003; P=.003), stride time variability (ß=.012; P=.02), stride length (ß=-.002; P=.004), and distance traveled (ß=-.786; P=.005). Nausea and pain explained 17% to 33% and 14% to 36% of gait variance measured in patients, respectively.

CONCLUSIONS

Patients scheduled to receive autoHSCT demonstrated worse mobility in multiple turning, gait, and balance domains compared with controls, potentially related in part to nausea and pain. Wearable inertial sensors used in the clinic setting could provide granular information about mobility before further treatment, which may in turn benefit from rehabilitation or symptom management. Future longitudinal studies are needed to better understand temporal changes in mobility and symptoms across the treatment trajectory to optimally time, design, and implement strategies, to preserve functioning in patients with hematologic cancer in the long term.

Fall Prediction Based on Instrumented Measures of Gait and Turning in Daily Life in People with Multiple Sclerosis

This study investigates the potential of passive monitoring of gait and turning in daily life in people with multiple sclerosis (PwMS) to identify those at future risk of falls. Seven days of passive monitoring of gait and turning were carried out in a pilot study of 26 PwMS in home settings using wearable inertial sensors. The retrospective fall history was collected at the baseline. After gait and turning data collection in daily life, PwMS were followed biweekly for a year and were classified as fallers if they experienced >1 fall. The ability of short-term passive monitoring of gait and turning, as well as retrospective fall history to predict future falls were compared using receiver operator curves and regression analysis. The history of retrospective falls was not identified as a significant predictor of future falls in this cohort (AUC = 0.62, p = 0.32). Among quantitative monitoring measures of gait and turning, the pitch at toe-off was the best predictor of falls (AUC = 0.86, p < 0.01). Fallers had a smaller pitch of their feet at toe-off, reflecting less plantarflexion during the push-off phase of walking, which can impact forward propulsion and swing initiation and can result in poor foot clearance and an increased metabolic cost of walking. In conclusion, our cohort of PwMS showed that objective monitoring of gait and turning in daily life can identify those at future risk of falls, and the pitch at toe-off was the single most influential predictor of future falls. Therefore, interventions aimed at improving the strength of plantarflexion muscles, range of motion, and increased proprioceptive input may benefit PwMS at future fall risk.

Inertial Sensor Algorithm to Estimate Walk Distance

The “total distance walked” obtained during a standardized walking test is an integral component of physical fitness and health status tracking in a range of consumer and clinical applications. Wearable inertial sensors offer the advantages of providing accurate, objective, and reliable measures of gait while streamlining walk test administration. The aim of this study was to develop an inertial sensor-based algorithm to estimate the total distance walked using older subjects with impaired fasting glucose (Study I), and to test the generalizability of the proposed algorithm in patients with Multiple Sclerosis (Study II). All subjects wore two inertial sensors (Opals by Clario-APDM Wearable Technologies) on their feet. The walking distance algorithm was developed based on 108 older adults in Study I performing a 400 m walk test along a 20 m straight walkway. The validity of the algorithm was tested using a 6-minute walk test (6MWT) in two sub-studies of Study II with different lengths of a walkway, 15 m (Study II-A, n = 24) and 20 m (Study II-B, n = 22), respectively. The start and turn around points were marked with lines on the floor while smaller horizontal lines placed every 1 m served to calculate the manual distance walked (ground truth). The proposed algorithm calculates the forward distance traveled during each step as the change in the horizontal position from each foot-flat period to the subsequent foot-flat period. The total distance walked is then computed as the sum of walk distances for each stride, including turns. The proposed algorithm achieved an average absolute error rate of 1.92% with respect to a fixed 400 m distance for Study I. The same algorithm achieved an absolute error rate of 4.17% and 3.21% with respect to an averaged manual distance for 6MWT in Study II-A and Study II-B, respectively. These results demonstrate the potential of an inertial sensor-based algorithm to estimate a total distance walked with good accuracy with respect to the manual, clinical standard. Further work is needed to test the generalizability of the proposed algorithm with different administrators and populations, as well as larger diverse cohorts.

Effectiveness of the Mobility Rehab System for Mobility Training in Older Adults: A Pragmatic Clinical Trial

Introduction: Mobility impairments are among the main causes of falls in older adults and patients with neurological diseases, leading to functional dependence and substantial health care costs. Feedback-based interventions applied in controlled, laboratory environments have shown promising results for mobility rehabilitation, enhancing the benefits of standard therapy. However, the effectiveness of sensor-based feedback to improve gait in actual outpatient physical therapy settings is unknown. The proposed trial examines the effectiveness of a physical therapist-assisted, visual feedback system using wearable inertial sensors, Mobility Rehab, for mobility training in older adults with gait disturbances in an outpatient clinic. Methods: The study is a single site, pragmatic clinical trial in older adults with gait disturbances. Two hundred patients undergoing their outpatient rehabilitation program are assigned, by an independent assistant, for screening by one of four therapists, and assigned to either a standard physical therapy or therapist-assisted feedback therapy. Both groups train twice a week for 6 weeks. Four physical therapists were randomized and stratified by years of experience to deliver standard therapy or therapist-assisted feedback rehabilitation. Each session is 45 min long. Gait is trained for 30 min. The additional 15 min include exercises for endurance, strength, and static and dynamic balance in functional tasks. Mobility Rehab uses unobtrusive, inertial sensors on the feet and belt with real-time algorithms to provide real-time feedback on gait metrics (i.e., gait speed, double support time, foot clearance, angle at foot strike, and arm swing), which are displayed on a hand-held monitor. Blinded assessments are carried out before and after the intervention. The primary outcome measure is subjects' perception of balance as measured by the Activities-specific Balance Confidence scale. Gait speed, as measured with wearable inertial sensors during walking, is the secondary outcome measure. Discussion: We hypothesize that therapist-assisted feedback rehabilitation will be more effective than standard rehabilitation for gait. Feedback of motor performance plays a crucial role in rehabilitation and objective characterization of gait impairments by Mobility Rehab has the potential to improve the accuracy of patient-specific gait feedback. Clinical Trial Registration:www.ClinicalTrials.gov, identifier: NCT03869879.

Gait Variability in Spinocerebellar Ataxia Assessed Using Wearable Inertial Sensors

BACKGROUND

Quantitative assessment of severity of ataxia-specific gait impairments from wearable technology could provide sensitive performance outcome measures with high face validity to power clinical trials.

OBJECTIVES

The aim of this study was to identify a set of gait measures from body-worn inertial sensors that best discriminate between people with prodromal or manifest spinocerebellar ataxia (SCA) and age-matched, healthy control subjects (HC) and determine how these measures relate to disease severity.

METHODS

One hundred and sixty-three people with SCA (subtypes 1, 2, 3, and 6), 42 people with prodromal SCA, and 96 HC wore 6 inertial sensors while performing a natural pace, 2-minute walk. Areas under the receiver operating characteristic curves (AUC) were compared for 25 gait measures, including standard deviations as variability, to discriminate between ataxic and normal gait. Pearson's correlation coefficient assessed the relationships between the gait measures and severity of ataxia.

RESULTS

Increased gait variability was the most discriminative gait feature of SCA; toe-out angle variability (AUC = 0.936; sensitivity = 0.871; specificity = 0.896) and double-support time variability (AUC = 0.932; sensitivity = 0.834; specificity = 0.865) were the most sensitive and specific measures. These variability measures were also significantly correlated with the scale for the assessment and rating of ataxia (SARA) and disease duration. The same gait measures discriminated gait of people with prodromal SCA from the gait of HC (AUC = 0.610, and 0.670, respectively).

CONCLUSIONS

Wearable inertial sensors provide sensitive and specific measures of excessive gait variability in both manifest and prodromal SCAs that are reliable and related to the severity of the disease, suggesting they may be useful as clinical trial performance outcome measures. © 2021 International Parkinson and Movement Disorder Society.

Does gait bout definition influence the ability to discriminate gait quality between people with and without multiple sclerosis during daily life?

BACKGROUND

There is currently no consensus about standardized gait bout definitions when passively monitoring walking during normal daily life activities. It is also not known how different definitions of a gait bout in daily life monitoring affects the ability to distinguish pathological gait quality. Specifically, how many seconds of a pause with no walking indicates an end to one gait bout and the start of another bout? In this study, we investigated the effect of 3 gait bout definitions on the discriminative ability to distinguish quality of walking in people with multiple sclerosis (MS) from healthy control subjects (HC) during a week of daily living.

METHODS

15 subjects with MS and 16 HC wore instrumented socks on each foot and one Opal sensor over the lower lumbar area for a week of daily activities for at least 8 h/day. Three gait bout definitions were based on the length of the pause between the end of one gait bout and start of another bout (1.25 s, 2.50 s, and 5.0 s pause). Area under the curve (AUC) was used to compare gait quality measures in MS versus HC.

RESULTS

Total number of gait bouts over the week were statistically significantly different across bout definitions, as expected. However, AUCs of gait quality measures (such as gait speed, stride length, stride time) discriminating people with MS from HC were not different despite the 3 bout definitions.

SIGNIFICANCE

Quality of gait measures that discriminate MS from HC during daily life are not influenced by the length of a gait bout, despite large differences in quantity of gait across bout definitions. Thus, gait quality measures in people with MS versus controls can be compared across studies using different gait bout definitions with pause lengths ≤5 s.

Laboratory versus daily life gait characteristics in patients with multiple sclerosis, Parkinson's disease, and matched controls

BACKGROUND AND PURPOSE

Recent findings suggest that a gait assessment at a discrete moment in a clinic or laboratory setting may not reflect functional, everyday mobility. As a step towards better understanding gait during daily life in neurological populations, we compared gait measures that best discriminated people with multiple sclerosis (MS) and people with Parkinson's Disease (PD) from their respective, age-matched, healthy control subjects (MS-Ctl, PD-Ctl) in laboratory tests versus a week of daily life monitoring.

METHODS

We recruited 15 people with MS (age mean ± SD: 49 ± 10 years), 16 MS-Ctl (45 ± 11 years), 16 people with idiopathic PD (71 ± 5 years), and 15 PD-Ctl (69 ± 7 years). Subjects wore 3 inertial sensors (one each foot and lower back) in the laboratory followed by 7 days during daily life. Mann-Whitney U test and area under the curve (AUC) compared differences between PD and PD-Ctl, and between MS and MS-Ctl in the laboratory and in daily life.

RESULTS

Participants wore sensors for 60-68 h in daily life. Measures that best discriminated gait characteristics in people with MS and PD from their respective control groups were different between the laboratory gait test and a week of daily life. Specifically, the toe-off angle best discriminated MS versus MS-Ctl in the laboratory (AUC [95% CI] = 0.80 [0.63-0.96]) whereas gait speed in daily life (AUC = 0.84 [0.69-1.00]). In contrast, the lumbar coronal range of motion best discriminated PD versus PD-Ctl in the laboratory (AUC = 0.78 [0.59-0.96]) whereas foot-strike angle in daily life (AUC = 0.84 [0.70-0.98]). AUCs were larger in daily life compared to the laboratory.

CONCLUSIONS

Larger AUC for daily life gait measures compared to the laboratory gait measures suggest that daily life monitoring may be more sensitive to impairments from neurological disease, but each neurological disease may require different gait outcome measures.

Inertial Sensor Algorithms to Characterize Turning in Neurological Patients With Turn Hesitations

BACKGROUND

One difficulty in turning algorithm design for inertial sensors is detecting two discrete turns in the same direction, close in time. A second difficulty is under-estimation of turn angle due to short-duration hesitations by people with neurological disorders. We aimed to validate and determine the generalizability of a: I. Discrete Turn Algorithm for variable and sequential turns close in time and II: Merged Turn Algorithm for a single turn angle in the presence of hesitations.

METHODS

We validated the Discrete Turn Algorithm with motion capture in healthy controls (HC, n = 10) performing a spectrum of turn angles. Subsequently, the generalizability of the Discrete Turn Algorithm and associated, Merged Turn Algorithm were tested in people with Parkinson's disease (PD, n = 124), spinocerebellar ataxia (SCA, n = 51), and HC (n = 125).

RESULTS

The Discrete Turn Algorithm shows improved agreement with optical motion capture and with known turn angles, compared to our previous algorithm by El-Gohary et al. The Merged Turn algorithm that merges consecutive turns in the same direction with short hesitations resulted in turn angle estimates closer to a fixed 180-degree turn angle in the PD, SCA, and HC subjects compared to our previous turn algorithm. Additional metrics were proposed to capture turn hesitations in PD and SCA.

CONCLUSION

The Discrete Turn Algorithm may be particularly useful to characterize turns when the turn angle is unknown, i.e., during free-living conditions. The Merged Turn algorithm is recommended for clinical tasks in which the single-turn angle is known, especially for patients who hesitate while turning.

Effect of Bout Length on Gait Measures in People with and without Parkinson's Disease during Daily Life

Although the use of wearable technology to characterize gait disorders in daily life is increasing, there is no consensus on which specific gait bout length should be used to characterize gait. Clinical trialists using daily life gait quality as study outcomes need to understand how gait bout length affects the sensitivity and specificity of measures to discriminate pathological gait as well as the reliability of gait measures across gait bout lengths. We investigated whether Parkinson's disease (PD) affects how gait characteristics change as bout length changes, and how gait bout length affects the reliability and discriminative ability of gait measures to identify gait impairments in people with PD compared to neurotypical Old Adults (OA). We recruited 29 people with PD and 20 neurotypical OA of similar age for this study. Subjects wore 3 inertial sensors, one on each foot and one over the lumbar spine all day, for 7 days. To investigate which gait bout lengths should be included to extract gait measures, we determined the range of gait bout lengths available across all subjects. To investigate if the effect of bout length on each gait measure is similar or not between subjects with PD and OA, we used a growth curve analysis. For reliability and discriminative ability of each gait measure as a function of gait bout length, we used the intraclass correlation coefficient (ICC) and area under the curve (AUC), respectively. Ninety percent of subjects walked with a bout length of less than 53 strides during the week, and the majority (>50%) of gait bouts consisted of less than 12 strides. Although bout length affected all gait measures, the effects depended on the specific measure and sometimes differed for PD versus OA. Specifically, people with PD did not increase/decrease cadence and swing duration with bout length in the same way as OA. ICC and AUC characteristics tended to be larger for shorter than longer gait bouts. Our findings suggest that PD interferes with the scaling of cadence and swing duration with gait bout length. Whereas control subjects gradually increased cadence and decreased swing duration as bout length increased, participants with PD started with higher than normal cadence and shorter than normal stride duration for the smallest bouts, and cadence and stride duration changed little as bout length increased, so differences between PD and OA disappeared for the longer bout lengths. Gait measures extracted from shorter bouts are more common, more reliable, and more discriminative, suggesting that shorter gait bouts should be used to extract potential digital biomarkers for people with PD.

A Two-Stage Tremor Detection Algorithm for Wearable Inertial Sensors During Normal Daily Activities

Continuous monitoring of tremor with wearable wrist sensors during normal daily activities is more difficult than in a clinical setting when subjects perform prescribed activities because some normal daily activities resemble tremor, many normal movements contain frequency content that overlaps with the tremor frequency, and the tremor amplitude has a large dynamic range during normal daily activities. We describe a novel two-stage algorithm that offers improvement at discriminating tremor from other activities. Some of this improvement is attained by using prior domain knowledge that tremor occurs over a narrow range of frequencies for an individual, but the mean tremor frequency may vary significantly between individuals in a study population. We validated the algorithm in continuous recordings from people with Parkinson's disease and matched control subjects. The algorithm has good face validity, a low rate of false positives on recordings from control subjects (<; 1.1%), and good correspondence with the constancy of rest tremor as measured by this question on the MDS-UPDRS (ρ = 0.54).

Quantity and quality of gait and turning in people with multiple sclerosis, Parkinson's disease and matched controls during daily living

Clinical trials need to specify which specific gait characteristics to monitor as mobility measures for each neurological disorder. As a first step, this study aimed to investigate a set of measures from daily-life monitoring that best discriminate mobility between people with multiple sclerosis (MS) and age-matched healthy control subjects (MS-Ctl) and between people with Parkinson's disease (PD) and age-matched healthy control subjects (PD-Ctl). Further, we investigated how these discriminative measures relate to the disease severity of MS or PD. We recruited 13 people with MS, 21 MS-Ctl, 29 people with idiopathic PD, and 20 PD-Ctl. Subjects wore 3 inertial sensors on their feet and the lumbar back for a week. The Area Under Curves (AUC) from the receiver operator characteristic (ROC) plot was calculated for each measure to determine the objective measures that best separated the MS and PD groups from their respective control cohorts. Adherence wearing the sensors was similar among groups for 58-66 h of recording (p = 0.14). Quantity of mobility (activity measures, such as a median number of strides per gait bout, AUC = 0.93) best discriminated mobility impairments in MS from MS-Ctl. In contrast, quality of mobility (such as turn angle, AUC = 0.90) best discriminated mobility impairments in PD from PD-Ctl. Mobility measures with AUC > 0.80 were correlated with MS and PD clinical scores of disease severity. Thus, measures characterizing mobility impairments differ for MS versus PD during daily life suggesting that mobility measures for clinical trials and clinical practice need to be specific to each neurological disorder.

The Sensor Technology and Rehabilitative Timing (START) Protocol: A Randomized Controlled Trial for the Rehabilitation of Mild Traumatic Brain Injury

BACKGROUND

Clinical practice for rehabilitation after mild traumatic brain injury (mTBI) is variable, and guidance on when to initiate physical therapy is lacking. Wearable sensor technology may aid clinical assessment, performance monitoring, and exercise adherence, potentially improving rehabilitation outcomes during unsupervised home exercise programs.

OBJECTIVE

The objectives of this study were to: (1) determine whether initiating rehabilitation earlier than typical will improve outcomes after mTBI, and (2) examine whether using wearable sensors during a home-exercise program will improve outcomes in participants with mTBI.

DESIGN

This was a randomized controlled trial.

SETTING

This study will take place within an academic hospital setting at Oregon Health & Science University and Veterans Affairs Portland Health Care System, and in the home environment.

PARTICIPANTS

This study will include 160 individuals with mTBI.

INTERVENTION

The early intervention group (n = 80) will receive one-on-one physical therapy 8 times over 6 weeks and complete daily home exercises. The standard care group (n = 80) will complete the same intervention after a 6- to 8-week wait period. One-half of each group will receive wearable sensors for therapist monitoring of patient adherence and quality of movements during their home exercise program.

MEASUREMENTS

The primary outcome measure will be the Dizziness Handicap Inventory score. Secondary outcome measures will include symptomatology, static and dynamic postural control, central sensorimotor integration posturography, and vestibular-ocular-motor function.

LIMITATIONS

Potential limitations include variable onset of care, a wide range of ages, possible low adherence and/or withdrawal from the study in the standard of care group, and low Dizziness Handicap Inventory scores effecting ceiling for change after rehabilitation.

CONCLUSIONS

If initiating rehabilitation earlier improves primary and secondary outcomes post-mTBI, this could help shape current clinical care guidelines for rehabilitation. Additionally, using wearable sensors to monitor performance and adherence may improve home exercise outcomes.

Digital Biomarkers of Mobility in Parkinson's Disease During Daily Living

BACKGROUND

Identifying digital biomarkers of mobility is important for clinical trials in Parkinson's disease (PD).

OBJECTIVE

To determine which digital outcome measures of mobility discriminate mobility in people with PD from healthy control (HC) subjects over a week of continuous monitoring.

METHODS

We recruited 29 people with PD, and 27 age-matched HC subjects. Subjects were asked to wear three inertial sensors (Opal by APDM) attached to both feet and to the lumbar region, and a subset of subjects also wore two wrist sensors, for a week of continuous monitoring. We derived 43 digital outcome measures of mobility grouped into five domains. An Area Under Curve (AUC) was calculated for each digital outcome measures of mobility, and logistic regression employing a 'best subsets selection strategy' was used to find combinations of measures that discriminated mobility in PD from HC.

RESULTS

Duration of recordings was 66±14 hours in the PD and 59±16 hours in the HC. Out of a total of 43 digital outcome measures of mobility, we found six digital outcome measures of mobility with AUC > 0.80. Turn angle (AUC = 0.89, 95% CI: 0.79-0.97) and swing time variability (AUC = 0.87, 95% CI: 0.75-0.96) were the most discriminative individual measures. Turning measures were most consistently selected via the best subsets strategy to discriminate people with PD from HC, followed by gait variability measures.

CONCLUSION

Clinical studies and clinical practice with digital biomarkers of daily life mobility in PD should include turning and variability measures.

The Impact Of Freezing Of Gait On Balance Perception And Mobility In Community-Living With Parkinson'S Disease

This pilot study investigated the impact of freezing of gait, objectively measured with three inertial sensors, on mobility function during seven days of communityliving monitoring in people with Parkinson's disease.Twenty-four subjects with PD, of which 14 experiencing freezing of gait, were recruited in this study. Subjects wore three inertial sensors (Opals, APDM) attached to both feet and the lumbar region for a week of continuous monitoring. Walking bouts, of at least 10s, were first identified, and then features of freezing, quantity and quality of mobility were extracted and averaged across the seven days.Results showed significant impairments in freezing and quality of mobility in the freezers group compared to the nonfreezers. Our measures of average and variability of time spent freezing was associated to the subjects' perception of freezing, assessed with the New Freezing of Gait Questionnaire. These preliminary results are introducing promising measures of mobility impairments measured during community-living in PD.

Validation of an Inertial Sensor Algorithm to Quantify Head and Trunk Movement in Healthy Young Adults and Individuals with Mild Traumatic Brain Injury

Wearable inertial measurement units (IMUs) may provide useful, objective information to clinicians interested in quantifying head movements as patients’ progress through vestibular rehabilitation. The purpose of this study was to validate an IMU-based algorithm against criterion data (motion capture) to estimate average head and trunk range of motion (ROM) and average peak velocity. Ten participants completed two trials of standing and walking tasks while moving the head with and without moving the trunk. Validity was assessed using a combination of Intra-class Correlation Coefficients (ICC), root mean square error (RMSE), and percent error. Bland-Altman plots were used to assess bias. Excellent agreement was found between the IMU and criterion data for head ROM and peak rotational velocity (average ICC > 0.9). The trunk showed good agreement for most conditions (average ICC > 0.8). Average RMSE for both ROM (head = 2.64°; trunk = 2.48°) and peak rotational velocity (head = 11.76 °/s; trunk = 7.37 °/s) was low. The average percent error was below 5% for head and trunk ROM and peak rotational velocity. No clear pattern of bias was found for any measure across conditions. Findings suggest IMUs may provide a promising solution for estimating head and trunk movement, and a practical solution for tracking progression throughout rehabilitation or home exercise monitoring.

Alteration parameters affecting the Luxor Avenue of the Sphinxes-Egypt

Stone alteration in the environment is caused by various extrinsic disintegration agents, besides, their intrinsic properties "mineralogical composition, textures and internal structure". Therefore, the purpose of the current study was to evaluate the weathering state affecting the Luxor Avenue of the Sphinxes by studying its chemical, mineralogical and physio-mechanical characteristics, in addition to morphological features. Scientific techniques, such as X-ray fluorescence (XRF), X-ray diffraction (XRD), Petrographical microscopy (PM), Cathodoluminescence (CL), Environmental Scanning Electron Microscope (ESEM) and micro energy-dispersive X-ray fluorescence (μ-EDXRF) were used. The results showed that quartz represents more than 96% of the sandstones and the main cement of the grains is quartz overgrowth. Alteration and formation of kaolinite was clearly observed. Halite, sylvite and bischofite were the main salts that affected the statues representing approx. 78.40%. The study also provided information about the different deterioration factors affected the Avenue of the Sphinxes namely; burial environment, solar effects, soil moisture and groundwater. These caused some deterioration forms such as soiling & crusting, breaking down most of the statues heads, saturation forms, salt crystallizations and stone abrasion. Cleaning, desalination and consolidation using different materials and techniques, in addition to reducing the human anthropogenic impacts are recommended for future conservation of the Luxor Avenue of the Sphinxes.

Wearable Inertial Sensors Allow for Quantitative Assessment of Shoulder and Elbow Kinematics in a Cadaveric Knee Arthroscopy Model

PURPOSE

To develop a model using wearable inertial sensors to assess the performance of orthopaedic residents while performing a diagnostic knee arthroscopy.

METHODS

Fourteen subjects performed a diagnostic arthroscopy on a cadaveric right knee. Participants were divided into novices (5 postgraduate year 3 residents), intermediates (5 postgraduate year 4 residents), and experts (4 faculty) based on experience. Arm movement data were collected by inertial measurement units (Opal sensors) by securing 2 sensors to each upper extremity (dorsal forearm and lateral arm) and 2 sensors to the trunk (sternum and lumbar spine). Kinematics of the elbow and shoulder joints were calculated from the inertial data by biomechanical modeling based on a sequence of links connected by joints. Range of motion required to complete the procedure was calculated for each group. Histograms were used to compare the distribution of joint positions for an expert, intermediate, and novice.

RESULTS

For both the right and left upper extremities, skill level corresponded well with shoulder abduction-adduction and elbow prono-supination. Novices required on average 17.2° more motion in the right shoulder abduction-adduction plane than experts to complete the diagnostic arthroscopy (P = .03). For right elbow prono-supination (probe hand), novices required on average 23.7° more motion than experts to complete the procedure (P = .03). Histogram data showed novices had markedly more variability in shoulder abduction-adduction and elbow prono-supination compared with the other groups.

CONCLUSIONS

Our data show wearable inertial sensors can measure joint kinematics during diagnostic knee arthroscopy. Range-of-motion data in the shoulder and elbow correlated inversely with arthroscopic experience. Motion pattern-based analysis shows promise as a metric of resident skill acquisition and development in arthroscopy.

CLINICAL RELEVANCE

Wearable inertial sensors show promise as metrics of arthroscopic skill acquisition among residents.

Inertial and time-of-arrival ranging sensor fusion

Wearable devices with embedded kinematic sensors including triaxial accelerometers, gyroscopes, and magnetometers are becoming widely used in applications for tracking human movement in domains that include sports, motion gaming, medicine, and wellness. The kinematic sensors can be used to estimate orientation, but can only estimate changes in position over short periods of time. We developed a prototype sensor that includes ultra wideband ranging sensors and kinematic sensors to determine the feasibility of fusing the two sensor technologies to estimate both orientation and position. We used a state space model and applied the unscented Kalman filter to fuse the sensor information. Our results demonstrate that it is possible to estimate orientation and position with less error than is possible with either sensor technology alone. In our experiment we obtained a position root mean square error of 5.2cm and orientation error of 4.8° over a 15min recording.

Continuous monitoring of turning in Parkinson's disease: Rehabilitation potential

BACKGROUND

Difficulty turning during gait is a major contributor to mobility disability, falls and reduced quality of life in patients with Parkinson's disease (PD). Unfortunately, the assessment of mobility in the clinic may not adequately reflect typical mobility function or its variability during daily life. We hypothesized that quality of turning mobility, rather than overall quantity of activity, would be impaired in people with PD over seven days of continuous recording.

METHODS

Thirteen subjects with PD and 8 healthy control subjects of similar age wore three Opal inertial sensors (on their belt and on each foot) throughout seven consecutive days during normal daily activities. Turning metrics included average and coefficient of variation (CV) of: (1) number of turns per hour, (2) turn angle amplitude, (3) turn duration, (4) turn mean velocity, and (5) number of steps per turn. Turning characteristics during continuous monitoring were compared with turning 90 and 180 degrees in a observed gait task.

RESULTS

No differences were found between PD and control groups for observed turns. In contrast, subjects with PD showed impaired quality of turning compared to healthy control subjects (Turn Mean Velocity: 43.3 ± 4.8°/s versus 38 ± 5.7°/s, mean number of steps 1.7 ± 1.1 versus 3.2 ± 0.8). In addition, PD patients showed higher variability within the day and across days compared to controls. However, no differences were seen between PD and control subjects in the overall activity (number of steps per day or percent of the day walking) during the seven days.

CONCLUSIONS

We show that continuous monitoring of natural turning during daily activities inside or outside the home is feasible for patients with PD and the elderly. This is the first study showing that continuous monitoring of turning was more sensitive to PD than observed turns. In addition, the quality of turning characteristics was more sensitive to PD than quantity of turns. Characterizing functional turning during daily activities will address a critical barrier to rehabilitation practice and clinical trials: objective measures of mobility characteristics in real-life environments.

Continuous Monitoring of Turning Mobility and Its Association to Falls and Cognitive Function: A Pilot Study

BACKGROUND

Difficulty turning is a major contributor to mobility disability, falls, and reduced quality of life in older people because it requires dynamic balance control that worsens with age. However, no study has quantified the quality and quantity of turning during normal daily activities in older people. The objective of this pilot study was to determine if quality of turning during daily activities is associated with falls and/or cognitive function.

METHODS

Thirty-five elderly participants (85 ± 8 years) wore three Opal inertial sensors. Turning and activity rate were measured. Based on retrospective falls, participants were grouped into nonfallers (N = 16), single fallers (N = 12), and recurrent fallers (N = 7). We also determined which turning characteristic predicted falls in the 6 months following the week of monitoring.

RESULTS

Quality of turning was significantly compromised in recurrent fallers compared with nonfallers (p < .05). In contrast, activity rate and mean number of turns per hour were similar across the three groups. Also, quality of turning during a prescribed test was similar across the three groups. Visuospatial and memory functions and the Tinetti Balance Scores were associated with quality of turning. Future falls were related to an increased variability of number of steps to turn.

CONCLUSIONS

Continuous monitoring of turning characteristics, while walking during daily activities, is feasible in older people. Turning characteristics during daily life appear to be more sensitive to fall risk than prescribed turning tasks. These findings suggest a slower, less variable, cautious turning strategy in elderly volunteers with a history of falls.

Human Joint Angle Estimation with Inertial Sensors and Validation with A Robot Arm

Traditionally, human movement has been captured primarily by motion capture systems. These systems are costly, require fixed cameras in a controlled environment, and suffer from occlusion. Recently, the availability of low-cost wearable inertial sensors containing accelerometers, gyroscopes, and magnetometers have provided an alternative means to overcome the limitations of motion capture systems. Wearable inertial sensors can be used anywhere, cannot be occluded, and are low cost. Several groups have described algorithms for tracking human joint angles. We previously described a novel approach based on a kinematic arm model and the Unscented Kalman Filter (UKF). Our proposed method used a minimal sensor configuration with one sensor on each segment. This paper reports significant improvements in both the algorithm and the assessment. The new model incorporates gyroscope and accelerometer random drift models, imposes physical constraints on the range of motion for each joint, and uses zero-velocity updates to mitigate the effect of sensor drift. A high-precision industrial robot arm precisely quantifies the performance of the tracker during slow, normal, and fast movements over continuous 15-min recording durations. The agreement between the estimated angles from our algorithm and the high-precision robot arm reference was excellent. On average, the tracker attained an RMS angle error of about 3(°) for all six angles. The UKF performed slightly better than the more common Extended Kalman Filter.

Continuous monitoring of turning in patients with movement disability

Difficulty with turning is a major contributor to mobility disability and falls in people with movement disorders, such as Parkinson's disease (PD). Turning often results in freezing and/or falling in patients with PD. However, asking a patient to execute a turn in the clinic often does not reveal their impairments. Continuous monitoring of turning with wearable sensors during spontaneous daily activities may help clinicians and patients determine who is at risk of falls and could benefit from preventative interventions. In this study, we show that continuous monitoring of natural turning with wearable sensors during daily activities inside and outside the home is feasible for people with PD and elderly people. We developed an algorithm to detect and characterize turns during gait, using wearable inertial sensors. First, we validate the turning algorithm in the laboratory against a Motion Analysis system and against a video analysis of 21 PD patients and 19 control (CT) subjects wearing an inertial sensor on the pelvis. Compared to Motion Analysis and video, the algorithm maintained a sensitivity of 0.90 and 0.76 and a specificity of 0.75 and 0.65, respectively. Second, we apply the turning algorithm to data collected in the home from 12 PD and 18 CT subjects. The algorithm successfully detects turn characteristics, and the results show that, compared to controls, PD subjects tend to take shorter turns with smaller turn angles and more steps. Furthermore, PD subjects show more variability in all turn metrics throughout the day and the week.

Upper limb joint angle tracking with inertial sensors

Wearable inertial systems have recently been used to track human movement in and outside of the laboratory. Continuous monitoring of human movement can provide valuable information relevant to individual's level of physical activity and functional ability. Traditionally, orientation has been calculated by integrating the angular velocity from gyroscopes. However, a small drift in the measured velocity leads to large integration errors that grow with time. To compensate for that drift, complementary data from accelerometers are normally fused into the tracking systems using the Kalman or extended Kalman filter (EKF). In this study, we combine kinematic models designed for control of robotic arms with the unscented Kalman filter (UKF) to continuously estimate the angles of human shoulder and elbow using two wearable sensors. This methodology can easily be generalized to track other human joints. We validate the method with an optical motion tracking system and demonstrate correlation consistently greater than 0.9 between the two systems.

Joint angle tracking with inertial sensors

Many wearable inertial systems have been used to continuously track human movement in and outside of a laboratory. The number of sensors and the complexity of the algorithms used to measure position and orientation vary according to the clinical application. To calculate changes in orientation, researchers often integrate the angular velocity. However, a relatively small error in measured angular velocity leads to large integration errors. This restricts the time of accurate measurement to a few minutes. We have combined kinematic models designed for control of robotic arms with state space methods to directly and continuously estimate the joint angles from inertial sensors. These algorithms can be applied to any combination of sensors, can easily handle malfunctions or the loss of some sensor inputs, and can be used in either a real-time or an off-line processing mode with higher accuracy.

User-guided interictal spike detection

In the diagnosis and treatment of epilepsy, long-term monitoring may be required to document and study interictal activities such as interictal spikes. However, visual inspection of the EEG done by an expert is too time consuming and researchers normally resort to automatic detection methods. We describe a new EEG user-guided interictal spike detection algorithm that only requires the user to annotate a few spikes. We use the annotations to build a template that captures the relevant features of spikes, and then use Mean Squared Error (MSE) test to detect all of the other spikes in the recording. The detected events are rank ordered so that the user can easily identify the true spikes and their time of occurrence. The true spikes are then annotated to the EEG signals and reported to the EEG expert for further evaluation. This design provides a compromise between the enormous time commitments necessary to annotate recordings by hand and the inability of fully-automatic spike detection algorithms to account for the variability between subjects. Because spike morphology and spatial distribution change considerably when patients go through cycles of wake and sleep in long-term monitoring, this detection algorithm uses multichannel multiple templates to detect more than one type of event. The algorithm is able to achieve an average sensitivity of 96% and an average of 4.8 false detections/ hour.

Health risk of bathing in Southern California coastal waters

Urbanized areas often discharge large volumes of contaminated waste into coastal waters, which may pose a health risk to bathers at nearby beach areas. In this investigation the authors estimated the number of gastrointestinal and respiratory illness episodes associated with the microbial contamination of coastal waters among bathers at Southern California beaches from 2000 through 2004. Bathers at the 67 beaches along the 350-km coastline of Southern California were the study population in this investigation. The authors' estimates were derived from a simulation model, which utilized water quality, beach attendance, and bathing-rate data, along with the three concentration-response relationships that underlie US Environmental Protection Agency, World Health Organization, and European Union marine water-quality guidelines. Given the absence of a general surveillance program to monitor these illnesses in Southern California, simulation modeling provides an established method to derive health risk estimates, despite additional analytic uncertainty that may accompany modeling-based analyses. An estimated 689,000 to 4,003,000 gastrointestinal illness episodes and 693,000 respiratory illness episodes occurred each year. The majority of illnesses (57% to 80%) occurred during the summer season as a result of large seasonal increases in beach attendance and bathing rates. As 71% of gastroenteritis episodes were estimated to occur when the water quality was considered safe for bathing, California's marine water-contact standards may be inadequate to protect the health of bathers.

Time delay and causality in biological systems using whitened cross-correlation analysis

In the study of biological systems, it is often desirable to study the relationship between two simultaneously recorded signals and investigate whether one signal is causing the other. Correlation between signals can be revealed by spectral analysis techniques such as coherence. While coherence reveals the interaction strength between two signals, it does not provide directional information about the direction of causality of the signals, if any. Cross-correlation can be reliably used to test whether a linear association exists between two processes. It can also be used to test whether a time lag exists between the signals by identifying the mean value of their cross-correlation sequence. In this paper, we propose applying a whitening filter to signals prior to estimating the cross-correlation. This whitening removes correlation of the signals with themselves, which generally blurs the cross-correlation over a broad range of lags and limits cross-correlation as a tool for causality analysis. In this application, a Kalman filter is used adaptively to whiten the signals. An example of the increased sensitivity of whitened cross-correlation analysis is given by studying the relationship between the mean intracranial pressure (ICP) and the heart rate (HR) of pediatric patients with traumatic brain injury. Results show that in five recordings from five patients, the heart rate process lags the mean intracranial pressure.

Deltamethrin-induced testicular apoptosis in rats: the protective effect of nitric oxide synthase inhibitor

This study is the first to examine and characterize the testicular apoptosis which might be induced due to exposure of male rats to deltamethrin. Furthermore, the role which might be played by nitric oxide (NO), as well as the other reactive oxygen species (ROS) in controlling this testicular apoptosis was assessed. Apoptosis was evaluated by DNA fragmentation detected by agarose gel electrophoresis and cellular morphology on testicular tissue sections. It was found that administration of deltamethrin (1 mg/kg daily for 21 days) to animals resulted in characteristic DNA migration patterns (laddering), thereby providing evidence that apoptosis is the major mechanism of cell death in the testicular tissues. In addition, histopathological examination of testicular tissue sections showed that apoptosis was confined to the basal germ cells, primary and secondary spermatocytes. These changes, in addition to the appearance of Sertoli cell vacuoles in deltamethrin-intoxicated animals, indicates the suppression of spermatogenesis. At the same time, the plasma levels of both NO and lipid peroxides measured as malondialdehyde (MDA) were found to be significantly increased in deltamethrin-treated animals. Administration of NO synthase (NOS) inhibitors such as N(G)-nitro monomethyl L-arginine hydrochloride (L-NMMA, 1 mg/kg) to rats 2 h before exposure to deltamethrin was effective in the reduction of the typically testicular apoptotic DNA fragmentation pattern and the associated histopathological changes. These findings may suggest that deltamethrin-induced testicular apoptosis is mediated by NO. Therefore, the pharmacological manipulation of apoptosis by selective NOS inhibitors such as L-NMMA may offer new possibilities for the control of deltamethrin-induced testicular dysfunction and infertility in the future.

Assessment of vinyl chloride-induced DNA damage in lymphocytes of plastic industry workers using a single-cell gel electrophoresis technique

DNA damage and the formation of stable carcinogen-DNA adducts are considered critical events in the initiation of the carcinogenic process. This study was carried out to assess whether exposure of plastics industry workers to the vinyl chloride monomer (VCM) for different periods of time would cause DNA damage, using the single-cell gel electrophoresis (SCGE) technique. Levels of DNA damage was assessed by both extent of DNA migration and numbers of DNA damaged spots in the peripheral blood lymphocytes from 32 plastics workers with different periods of exposure to VCM; they were evaluated by comparison with a group of non-exposed individuals. It was found that plastics workers who were exposed to VCM for different periods of time showed significantly increased levels of DNA damage compared with the non-exposed subjects. There was a significant correlation between the severity of DNA damage and duration of exposure. However, no significant correlation was found between the age of all subjects and DNA damage. Concentrations of VCM in the air inside the factory were found to be significantly higher than values in non-exposed areas, despite being lower than the threshold limit value (TLV). Our results encourage the application of SCGE as a sensitive, simple, fast and useful technique in the regular health screening of workers occupationally exposed to VCM (even at concentrations below the TLV) to assess the possibility of any DNA damage.

In vivo and in vitro evaluation of the mutagenic potential of carbamazepine: does melatonin have anti-mutagenic activity?

The mutagenic potential of carbamazepine (CBZ) therapy has been evaluated both in vivo and in vitro. Analysis of chromosome aberrations (CA), sister chromatid exchanges (SCEs), mitotic and proliferation indices (PRI) were performed. The in vivo study was carried out on 30 patients with idiopathic epilepsy end undergoing treatment with CBZ for different periods starting from 6 months up to 15 years. Plasma CBZ levels were also determined for each patient. The results showed that the total CA and SCEs were significantly increased in CBZ-treated patients. There was no significant correlation between CA and either duration of treatment or the plasma CBZ levels for each patient. The mitotic and proliferation indices were found to be slightly but non-significantly decreased compared to control values. On the other hand, in vitro analysis showed a significant dose-dependent increase in CA and SCEs in human lymphocyte cultures treated with CBZ (4-12 microg/ml). The mitotic and proliferation indices were also found to be decreased but only significantly in case of high doses of CBZ (12 microg/ml). Pretreatment of human lymphocytes with melatonin (0.5 mM) exhibited a significant decrease in the frequencies of CBZ-induced CA and SCEs as compared with non-treated cultures. The depressed mitotic and proliferation indices were also found to be improved in cultures pretreated with melatonin. In conclusion, these observations suggest that CBZ monotherapy may lead to chromosome damaging effects (genotoxic) and the use of melatonin as anti-mutagenic agent for human protection against CBZ-induced chromosome damage should be considered.