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1.
Sci Rep ; 14(1): 8402, 2024 04 10.
Article in English | MEDLINE | ID: mdl-38600212

ABSTRACT

To maintain current cognitive function and access greater cognitive reserves, nonpharmacological interventions may be a viable alternative for older adults with or without cognitive impairment. This study aimed to compare different nonpharmacological interventions for enhancing global cognition, including mind-body exercise, physical exercise, non-invasive brain stimulation, cognitive training intervention (CTI), acutherapy (ACU), meditation, and music therapy, by applying a network meta-analysis (NMA). Sixty-one randomized controlled trials evaluating the efficacy of interventions on global cognition in older adults with or without mild cognitive decline were selected. An NMA was conducted to compare the efficacy of different nonpharmacological interventions. The NMA revealed that mind-body exercise (standardized mean difference, 1.384; 95% confidence interval, 0.777-1.992); ACU (1.283; 0.478-2.088); meditation (0.910; 0.097-1.724); non-invasive brain stimulation (1.242; 0.254-2.230); CTI (1.269; 0.736-1.802); and physical exercise (0.977; 0.212-1.742), showed positive effects compared to passive controls. There were no significant differences between the efficacies of other interventions. Nonpharmacological interventions may potentially enhance and maintain global cognition through various pathways, such as memorizing movements and enhancing brain plasticity by reducing stress in the older adult population. Additional studies are needed to clarify the impact of other variables, including intervention methods or psychological variables.


Subject(s)
Cognitive Dysfunction , Meditation , Humans , Aged , Network Meta-Analysis , Randomized Controlled Trials as Topic , Cognitive Dysfunction/therapy , Cognitive Dysfunction/psychology , Cognition/physiology , Exercise Therapy
2.
Alzheimers Res Ther ; 16(1): 83, 2024 Apr 13.
Article in English | MEDLINE | ID: mdl-38615028

ABSTRACT

BACKGROUND: The worldwide trend of demographic aging highlights the progress made in healthcare, albeit with health challenges like Alzheimer's Disease (AD), prevalent in individuals aged 65 and above. Its early detection at the mild cognitive impairment (MCI) stage is crucial. Event-related potentials (ERPs) obtained by averaging EEG segments responded to repeated events are vital for cognitive impairment research. Consequently, examining intra-trial ERP variability is vital for comprehending fluctuations within psychophysiological processes of interest. This study aimed to investigate cognitive deficiencies and instability in MCI using ERP variability and its asymmetry from a prefrontal two-channel EEG device. METHODS: In this study, ERP variability for both target and non-target responses was examined using the response variance curve (RVC) in a sample comprising 481 participants with MCI and 1,043 age-matched healthy individuals. The participants engaged in auditory selective attention tasks. Cognitive decline was assessed using the Seoul Neuropsychological Screening Battery (SNSB) and the Mini-Mental State Examination (MMSE). The research employed various statistical methods, including independent t-tests, and univariate and multiple logistic regression analyses. These analyses were conducted to investigate group differences and explore the relationships between neuropsychological test results, ERP variability and its asymmetry measures, and the prevalence of MCI. RESULTS: Our results showed that patients with MCI exhibited unstable cognitive processing, characterized by increased ERP variability compared to cognitively normal (CN) adults. Multiple logistic regression analyses confirmed the association between ERP variability in the target and non-target responses with MCI prevalence, independent of demographic and neuropsychological factors. DISCUSSION: The unstable cognitive processing in the MCI group compared to the CN individuals implies abnormal neurological changes and reduced and (or) unstable attentional maintenance during cognitive processing. Consequently, utilizing ERP variability measures from a portable EEG device could serve as a valuable addition to the conventional ERP measures of latency and amplitude. This approach holds significant promise for identifying mild cognitive deficits and neural alterations in individuals with MCI.


Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Adult , Humans , Biomarkers , Cognitive Dysfunction/diagnosis , Electroencephalography
3.
Sensors (Basel) ; 24(7)2024 Apr 08.
Article in English | MEDLINE | ID: mdl-38610573

ABSTRACT

A force plate is mainly used in biomechanics; it aims to measure the ground reaction force in a person's walking or standing position. In this study, a large-area force mat of the piezoresistance sensing type was developed, and a deep-learning-based weight measurement calibration method was applied to solve the problem in which measurements are not normalized because of physical limitations in hardware and signal processing. The test set was composed of the values measured at each point by weight and the value of the center of the pressure variable, and the measured value was predicted using a deep neural network (DNN) regression model. The calibration verification results show that the average weight errors range from a minimum of 0.06% to a maximum of 3.334%. This is simpler than the previous method, which directly measures the ratio of the resistance value to the measured weight of each sensor and derives an equation.

4.
Front Aging Neurosci ; 16: 1307204, 2024.
Article in English | MEDLINE | ID: mdl-38327500

ABSTRACT

We investigated a screening method for mild cognitive impairment (MCI) that combined bioimpedance features and the Korean Mini-Mental State Examination (K-MMSE) score. Data were collected from 539 subjects aged 60 years or older at the Gwangju Alzheimer's & Related Dementias (GARD) Cohort Research Center, A total of 470 participants were used for the analysis, including 318 normal controls and 152 MCI participants. We measured bioimpedance, K-MMSE, and the Seoul Neuropsychological Screening Battery (SNSB-II). We developed a multiple linear regression model to predict MCI by combining bioimpedance variables and K-MMSE total score and compared the model's accuracy with SNSB-II domain scores by the area under the receiver operating characteristic curve (AUROC). We additionally compared the model performance with several machine learning models such as extreme gradient boosting, random forest, support vector machine, and elastic net. To test the model performances, the dataset was divided into a training set (70%) and a test set (30%). The AUROC values of SNSB-II scores were 0.803 in both sexes, 0.840 for males, and 0.770 for females. In the combined model, the AUROC values were 0.790 (0.773) for males (and females), which were significantly higher than those from the model including MMSE scores alone (0.723 for males and 0.622 for females) or bioimpedance variables alone (0.640 for males and 0.615 for females). Furthermore, the accuracies of the combined model were comparable to those of machine learning models. The bioimpedance-MMSE combined model effectively distinguished the MCI participants and suggests a technique for rapid and improved screening of the elderly population at risk of cognitive impairment.

5.
Article in English | MEDLINE | ID: mdl-38083172

ABSTRACT

Alzheimer's disease (AD) is the leading cause of Dementia, and mild cognitive impairment (MCI) is often considered a precursor to the development of AD dementia and other types of Dementia. Biomarkers such as amyloid beta are specific and sensitive in identifying AD and can identify individuals who have biological evidence of the disease but have no symptoms, but clinicians and researchers may not easily use them on a large scale. Ocular biomarkers, such as those obtained through eye tracking (ET) technology, have the potential as a diagnostic tool due to their accuracy, affordability, and ease of use. In this study, we show that eye movement (EM) metrics from an interleaved Pro/Anti-saccade (PS/AS) ET task can differentiate between cognitively normal (CN) and MCI subjects and that the presence of Aß brain deposits, a biomarker of AD, significantly affects performance on these tasks. Individuals with Aß deposits (Aß+) performed worse than those without (Aß-). Our findings suggest that eye-tracking measurements may be a valuable tool for detecting amyloid brain pathology and monitoring changes in cognitive function in CN and MCI individuals over time.Clinical Relevance- The PS/AS paradigm, which measures saccadic eye movements, can accurately detect subtle cognitive impairments and changes in the brain associated with Alzheimer's disease in CN and MCI individuals. This makes it a valuable tool for identifying individuals at risk for cognitive decline and tracking changes in cognitive function over time.


Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Humans , Aged , Alzheimer Disease/diagnosis , Amyloid beta-Peptides , Saccades , Cognitive Dysfunction/diagnosis , Biomarkers
6.
Front Aging Neurosci ; 15: 1333781, 2023.
Article in English | MEDLINE | ID: mdl-38076530

ABSTRACT

[This corrects the article DOI: 10.3389/fnagi.2023.1273008.].

7.
Front Aging Neurosci ; 15: 1273008, 2023.
Article in English | MEDLINE | ID: mdl-37927335

ABSTRACT

Background: Alzheimer's disease (AD) is among the leading contributors of dementia globally with approximately 60-70% of its cases. Current research is focused on the mild cognitive impairment (MCI), which is associated with cognitive decline but does not disrupt routine activities. Event-related potential (ERP) research is essential in screening patients with MCI. Low-density channel electroencephalography (EEG) is frequently used due to its convenience, portability, and affordability, making it suitable for resource-constrained environments. Despite extensive research on neural biomarkers for cognitive impairment, there is a considerable gap in understanding the effects on early stages of cognitive processes, particularly when combining physiological and cognitive markers using portable devices. The present study aimed to examine cognitive shortfalls and behavioral changes in patients with MCI using prefrontal selective attention ERP recorded from a prefrontal two-channel EEG device. Methods: We assessed cognitive decline using the Mini-Mental State Examination (MMSE) and the Seoul Neuropsychological Screening Battery (SNSB). We administered auditory selective attention tasks to 598 elderly participants, including those with MCI (160) and cognitively normal (CN) individuals (407). We conducted statistical analyses such as independent t-tests, Pearson's correlations, and univariate and multiple logistic regression analyses to assess group differences and associations between neuropsychological tests, ERP measures, behavioral measures, and MCI prevalence. Results: Our findings revealed that patients with MCI demonstrated slower information-processing abilities, and exhibited poorer task execution, characterized by reduced accuracy, increased errors, and higher variability in response time, compared to CN adults. Multiple logistic regression analyses confirmed the association between some ERP and behavioral measures with MCI prevalence, independent of demographic and neuropsychological factors. A relationship was observed between neuropsychological scores, ERP, and behavioral measures. Discussion: The slower information processing abilities, and poor task execution in the MCI group compared to the CN individuals suggests flawed neurological changes and reduced attentional maintenance during cognitive processing, respectively. Hence, the utilization of portable EEG devices to capture prefrontal selective attention ERPs, in combination with behavioral assessments, holds promise for the identification of mild cognitive deficits and neural alterations in individuals with MCI. This approach could potentially augment the traditional neuropsychological tests during clinical screening for MCI.

8.
Sci Rep ; 13(1): 13389, 2023 08 17.
Article in English | MEDLINE | ID: mdl-37591966

ABSTRACT

This study examined the alterations of segmental body composition in individuals with Alzheimer's pathology (AD), including mild cognitive impairment (MCI) and dementia. A multifrequency bioimpedance analysis (BIA) was used to provide segmental water and impedance variables from 365 cognitively normal (CN), 123 MCI due to AD, and 30 AD dementia participants. We compared the BIA variables between the three groups, examined their correlations with neuropsychological screening test scores, and illustrate their 95% confidence RXc graphs. AD dementia participants were older, more depressive, and had worse cognitive abilities than MCI due to AD and CN participants. Although the BIA variables showed weak partial correlations with the cognitive test scores, we found patterns of an increasing water content in lean mass, increasing extra to intracellular water ratio, and decreasing reactance and phase angle in the lower extremities with effect sizes ranging from 0.26 to 0.51 in the groups of MCI and dementia due to AD compared with CN individuals. The RXc graphs upheld the findings with a significant displacement downward and toward the right, dominantly in the lower extremities. Individuals with AD pathology exhibit a reduced body cell mass or cell strength, an abnormal cellular water distribution, and an overhydration status in lean mass, especially in the lower extremities.


Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Humans , Lower Extremity , Cognition , Water
9.
Front Neurosci ; 17: 1171417, 2023.
Article in English | MEDLINE | ID: mdl-37397453

ABSTRACT

Background: Early identification of patients at risk of dementia, alongside timely medical intervention, can prevent disease progression. Despite their potential clinical utility, the application of diagnostic tools, such as neuropsychological assessments and neuroimaging biomarkers, is hindered by their high cost and time-consuming administration, rendering them impractical for widespread implementation in the general population. We aimed to develop non-invasive and cost-effective classification models for predicting mild cognitive impairment (MCI) using eye movement (EM) data. Methods: We collected eye-tracking (ET) data from 594 subjects, 428 cognitively normal controls, and 166 patients with MCI while they performed prosaccade/antisaccade and go/no-go tasks. Logistic regression (LR) was used to calculate the EM metrics' odds ratios (ORs). We then used machine learning models to construct classification models using EM metrics, demographic characteristics, and brief cognitive screening test scores. Model performance was evaluated based on the area under the receiver operating characteristic curve (AUROC). Results: LR models revealed that several EM metrics are significantly associated with increased odds of MCI, with odds ratios ranging from 1.213 to 1.621. The AUROC scores for models utilizing demographic information and either EM metrics or MMSE were 0.752 and 0.767, respectively. Combining all features, including demographic, MMSE, and EM, notably resulted in the best-performing model, which achieved an AUROC of 0.840. Conclusion: Changes in EM metrics linked with MCI are associated with attentional and executive function deficits. EM metrics combined with demographics and cognitive test scores enhance MCI prediction, making it a non-invasive, cost-effective method to identify early stages of cognitive decline.

10.
Front Aging Neurosci ; 15: 1131857, 2023.
Article in English | MEDLINE | ID: mdl-37032818

ABSTRACT

Background: Early screening of elderly individuals who are at risk of dementia allows timely medical interventions to prevent disease progression. The portable and low-cost electroencephalography (EEG) technique has the potential to serve it. Objective: We examined prefrontal EEG and event-related potential (ERP) variables in association with the predementia stages of Alzheimer's disease (AD). Methods: One hundred elderly individuals were recruited from the GARD cohort. The participants were classified into four groups according to their amyloid beta deposition (A+ or A-) and neurodegeneration status (N+ or N-): cognitively normal (CN; A-N-, n = 27), asymptomatic AD (aAD; A + N-, n = 15), mild cognitive impairment (MCI) with AD pathology (pAD; A+N+, n = 16), and MCI with non-AD pathology (MCI(-); A-N+, n = 42). Prefrontal resting-state eyes-closed EEG measurements were recorded for five minutes and auditory ERP measurements were recorded for 8 min. Three variables of median frequency (MDF), spectrum triangular index (STI), and positive-peak latency (PPL) were employed to reflect EEG slowing, temporal synchrony, and ERP latency, respectively. Results: Decreasing prefrontal MDF and increasing PPL were observed in the MCI with AD pathology. Interestingly, after controlling for age, sex, and education, we found a significant negative association between MDF and the aAD and pAD stages with an odds ratio (OR) of 0.58. Similarly, PPL exhibited a significant positive association with these AD stages with an OR of 2.36. Additionally, compared with the MCI(-) group, significant negative associations were demonstrated by the aAD group with STI and those in the pAD group with MDF with ORs of 0.30 and 0.42, respectively. Conclusion: Slow intrinsic EEG oscillation is associated with MCI due to AD, and a delayed ERP peak latency is likely associated with general cognitive impairment. MCI individuals without AD pathology exhibited better cortical temporal synchronization and faster EEG oscillations than those with aAD or pAD. Significance: The EEG/ERP variables obtained from prefrontal EEG techniques are associated with early cognitive impairment due to AD and non-AD pathology. This result suggests that prefrontal EEG/ERP metrics may serve as useful indicators to screen elderly individuals' early stages on the AD continuum as well as overall cognitive impairment.

11.
Front Nutr ; 9: 1006423, 2022.
Article in English | MEDLINE | ID: mdl-36185643

ABSTRACT

[This corrects the article DOI: 10.3389/fnut.2022.873623.].

12.
Front Nutr ; 9: 873623, 2022.
Article in English | MEDLINE | ID: mdl-35719147

ABSTRACT

Objective: To examine the changes in body composition, water compartment, and bioimpedance in mild cognitive impairment (MCI) individuals. Methods: We obtained seven whole-body composition variables and seven pairs of segmental body composition, water compartment, and impedance variables for the upper and lower extremities from the segmental multi-frequency bioelectrical impedance analysis (BIA) of 939 elderly participants, including 673 cognitively normal (CN) people and 266 individuals with MCI. Participants' characteristics, anthropometric information, and the selected BIA variables were described and statistically compared between the CN participants and those with MCI. The correlations between the selected BIA variables and neuropsychological tests such as the Korean version of the Mini-Mental State Examination and Seoul Neuropsychological Screening Battery - Second Edition were also examined before and after controlling for age and sex. Univariate and multivariate logistic regression analyses with estimated odds ratios (ORs) were conducted to investigate the associations between these BIA variables and MCI prevalence for different sexes. Results: Participants with MCI were slightly older, more depressive, and had significantly poorer cognitive abilities when compared with the CN individuals. The partial correlations between the selected BIA variables and neuropsychological tests upon controlling for age and sex were not greatly significant. However, after accounting for age, sex, and the significant comorbidities, segmental lean mass, water volume, resistance, and reactance in the lower extremities were positively associated with MCI, with ORs [95% confidence interval (CI)] of 1.33 (1.02-1.71), 1.33 (1.03-1.72), 0.76 (0.62-0.92), and 0.79 (0.67-0.93), respectively; with presumably a shift of water from the intracellular area to extracellular space. After stratifying by sex, resistance and reactance in lower extremities remained significant only in the women group. Conclusion: An increase in segmental water along with segmental lean mass and a decrease in body cell strength due to an abnormal cellular water distribution demonstrated by reductions in resistance and reactance are associated with MCI prevalence, which are more pronounced in the lower extremities and in women. These characteristic changes in BIA variables may be considered as an early sign of cognitive impairment in the elderly population.

13.
Front Aging Neurosci ; 14: 871432, 2022.
Article in English | MEDLINE | ID: mdl-35478701

ABSTRACT

Background: Mild cognitive impairment (MCI) may occur due to several forms of neurodegenerative diseases and non-degenerative conditions and is associated with cognitive impairment that does not affect everyday activities. For a timely diagnosis of MCI to prevent progression to dementia, a screening tool of fast, low-cost and easy access is needed. Recent research on eye movement hints it a potential application for the MCI screening. However, the precise extent of cognitive function decline and eye-movement control alterations in patients with MCI is still unclear. Objective: This study examined executive control deficits and saccade behavioral changes in patients with MCI using comprehensive neuropsychological assessment and interleaved saccade paradigms. Methods: Patients with MCI (n = 79) and age-matched cognitively healthy controls (HC) (n = 170) completed four saccadic eye-movement paradigms: prosaccade (PS)/antisaccade (AS), Go/No-go, and a battery of neuropsychological tests. Results: The findings revealed significantly longer latency in patients with MCI than in HC during the PS task. Additionally, patients with MCI had a lower proportion of correct responses and a marked increase in inhibition errors for both PS/AS and Go/No-go tasks. Furthermore, when patients with MCI made errors, they failed to self-correct many of these inhibition errors. In addition to the increase in inhibition errors and uncorrected inhibition errors, patients with MCI demonstrated a trend toward increased correction latencies. We also showed a relationship between neuropsychological scores and correct and error saccade responses. Conclusion: Our results demonstrate that, similar to patients with Alzheimer's dementia (AD), patients with MCI generate a high proportion of erroneous saccades toward the prepotent target and fail to self-correct many of these errors, which is consistent with an impairment of inhibitory control and error monitoring. Significance: The interleaved PS/AS and Go/No-go paradigms are sensitive and objective at detecting subtle cognitive deficits and saccade changes in MCI, indicating that these saccadic eye movement paradigms have clinical potential as a screening tool for MCI.

14.
Neuropsychol Rev ; 32(2): 193-227, 2022 06.
Article in English | MEDLINE | ID: mdl-33959887

ABSTRACT

Alzheimer's disease (AD) is the leading cause of dementia, and mild cognitive impairment (MCI) is considered the transitional state to AD dementia (ADD) and other types of dementia, whose symptoms are accompanied by altered eye movement. In this work, we reviewed the existing literature and conducted a meta-analysis to extract relevant eye movement parameters that are significantly altered owing to ADD and MCI. We conducted a systematic review of 35 eligible original publications in saccade paradigms and a meta-analysis of 27 articles with specified task conditions, which used mainly gap and overlap conditions in both prosaccade and antisaccade paradigms. The meta-analysis revealed that prosaccade and antisaccade latencies and frequency of antisaccade errors showed significant alterations for both MCI and ADD. First, both prosaccade and antisaccade paradigms differentiated patients with ADD and MCI from controls, however, antisaccade paradigms was more effective than prosaccade paradigms in distinguishing patients from controls. Second, during prosaccade in the gap and overlap conditions, patients with ADD had significantly longer latencies than patients with MCI, and the trend was similar during antisaccade in the gap condition as patients with ADD had significantly more errors than patients with MCI. The anti-effect magnitude was similar between controls and patients, and the magnitude of the latency of the gap effect varied among healthy controls and MCI and ADD subjects, but the effect size of the latency remained large in both patients. These findings suggest that, using gap effect, anti-effect, and specific choices of saccade paradigms and conditions, distinctions could be made between MCI and ADD patients as well as between patients and controls.


Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Alzheimer Disease/diagnosis , Cognitive Dysfunction/diagnosis , Humans , Saccades
15.
Sensors (Basel) ; 21(23)2021 Nov 23.
Article in English | MEDLINE | ID: mdl-34883786

ABSTRACT

Non-invasive measurement of physiological parameters and indicators, specifically among the elderly, is of utmost importance for personal health monitoring. In this study, we focused on photoplethysmography (PPG), and developed a regression model that calculates variables from the second (SDPPG) and third (TDPPG) derivatives of the PPG pulse that can observe the inflection point of the pulse wave measured by a wearable PPG device. The PPG pulse at the earlobe was measured for 3 min in 84 elderly Korean women (age: 71.19 ± 6.97 years old). Based on the PPG-based cardiovascular function, we derived additional variables from TDPPG, in addition to the aging variable to predict the age. The Aging Index (AI) from SDPPG and Sum of TDPPG variables were calculated in the second and third differential forms of PPG. The variables that significantly correlated with age were c/a, Tac, AI of SDPPG, sum of TDPPG, and correlation coefficient 'r' of the model. In multiple linear regression analysis, the r value of the model was 0.308, and that using deep learning on the model was 0.839. Moreover, the possibility of improving the accuracy of the model using supervised deep learning techniques, rather than the addition of datasets, was confirmed.


Subject(s)
Photoplethysmography , Wearable Electronic Devices , Aged , Aging , Female , Heart Rate , Humans , Linear Models , Middle Aged , Signal Processing, Computer-Assisted
16.
Front Aging Neurosci ; 13: 659817, 2021.
Article in English | MEDLINE | ID: mdl-33927610

ABSTRACT

Objective: To examine whether prefrontal electroencephalography (EEG) can be used for screening dementia. Methods: We estimated the global cognitive decline using the results of Mini-Mental Status Examination (MMSE), measurements of brain activity from resting-state EEG, responses elicited by auditory stimulation [sensory event-related potential (ERP)], and selective attention tasks (selective-attention ERP) from 122 elderly participants (dementia, 35; control, 87). We investigated that the association between MMSE and each EEG/ERP variable by using Pearson's correlation coefficient and performing univariate linear regression analysis. Kernel density estimation was used to examine the distribution of each EEG/ERP variable in the dementia and non-dementia groups. Both Univariate and multiple logistic regression analyses with the estimated odds ratios were conducted to assess the associations between the EEG/ERP variables and dementia prevalence. To develop the predictive models, five-fold cross-validation was applied to multiple classification algorithms. Results: Most prefrontal EEG/ERP variables, previously known to be associated with cognitive decline, show correlations with the MMSE score (strongest correlation has |r| = 0.68). Although variables such as the frontal asymmetry of the resting-state EEG are not well correlated with the MMSE score, they indicate risk factors for dementia. The selective-attention ERP and resting-state EEG variables outperform the MMSE scores in dementia prediction (areas under the receiver operating characteristic curve of 0.891, 0.824, and 0.803, respectively). In addition, combining EEG/ERP variables and MMSE scores improves the model predictive performance, whereas adding demographic risk factors do not improve the prediction accuracy. Conclusion: Prefrontal EEG markers outperform MMSE scores in predicting dementia, and additional prediction accuracy is expected when combining them with MMSE scores. Significance: Prefrontal EEG is effective for screening dementia when used independently or in combination with MMSE.

17.
Article in English | MEDLINE | ID: mdl-33804164

ABSTRACT

We developed two distinct forest therapy programs (FTPs) and compared their effects on dementia prevention and related health problems for older adults. One was focused on Qigong practice in the forest (QP) and the other involved active walking in the forest (WP). Both FTPs consisted of twelve 2-h sessions over six weeks and were conducted in an urban forest. We obtained data from 25, 18, and 26 participants aged 65 years or above for the QP, WP, and control groups, respectively. Neuropsychological scores via cognition (MoCA), geriatric depression (GDS) and quality of life (EQ-5D), and electrophysiological variables (electroencephalography, bioimpedance, and heart rate variability) were measured. We analyzed the intervention effects with a generalized linear model. Compared to the control group, the WP group showed benefits in terms of neurocognition (increases in the MoCA score, and alpha and beta band power values in the electroencephalogram), sympathetic nervous activity, and bioimpedance in the lower body. On the other hand, the QP group showed alleviated depression and an increased bioimpedance phase angle in the upper body. In conclusion, both active walking and Qigong in the forest were shown to have distinctive neuropsychological and electrophysiological benefits, and both had beneficial effects in terms of preventing dementia and relieving related health problems for elderly individuals.


Subject(s)
Qigong , Walking , Aged , Forests , Heart Rate , Humans , Quality of Life
18.
J Diabetes Investig ; 12(5): 790-802, 2021 May.
Article in English | MEDLINE | ID: mdl-32902171

ABSTRACT

AIMS/INTRODUCTION: We carried out a multicenter clinical study to investigate whether the decrease in segmental phase angles (PhA values) observed using bioelectrical impedance is useful in screening for diabetes mellitus and monitoring disease progression. MATERIALS AND METHODS: The segmental PhA values of the four limbs were acquired using multifrequency bioimpedance at 5, 50 and 250 kHz in three clinics. Differences in PhA values between the diabetes and control groups were analyzed using the two-sample t-test and analysis of variance (anova). Changes in PhA values with increasing durations of diabetes were analyzed using a moderated mediation model and multivariate linear regression analysis. We recruited 217 participants aged ≥40 years (diabetes 158, controls 59, men 106, women 111, A-clinic 71, B-clinic 70 and C-clinic 76). RESULTS: PhA values at 50 kHz were significantly decreased in people with diabetes (PhA of the right arm in men: t-value -4.0, P < 0.001; PhA of the right leg in women: t-value -4.6 P < 0.001), and the difference was partially attributable to the duration of diabetes, as well as aging. Specifically, the mediation effect of the duration of diabetes on the decrease in PhA values was 29.8% in the left arm of men, 53.3% in the right arm of women, and 36.3% in the left arm of both sexes. CONCLUSIONS: Phase angle values at 50 kHz decreased in people with diabetes, and the changes were exacerbated as the disease duration increased. Thus, bioimpedance PhA values represent a non-invasive tool for monitoring the progression of diabetes mellitus.


Subject(s)
Diabetes Mellitus/ethnology , Diabetes Mellitus/physiopathology , Electric Impedance , Time Factors , Aged , Aging/ethnology , Aging/physiology , Analysis of Variance , Arm/physiopathology , Case-Control Studies , Disease Progression , Female , Humans , Leg/physiopathology , Linear Models , Male , Mediation Analysis , Middle Aged , Republic of Korea/ethnology
19.
Sensors (Basel) ; 20(24)2020 Dec 21.
Article in English | MEDLINE | ID: mdl-33371295

ABSTRACT

This study describe the characteristics of hemiplegic stroke gait with principal component analysis (PCA) of trunk movement (TM) and gait event (GE) parameters by the inertial measurement unit (IMU) sensors: (1) Background: This process can determine dominant variables through multivariate examination to identify the affected, unaffected, and healthy lower-limb sides; (2) Methods: The study monitored forty patients with stroke and twenty-eight healthy individuals comprising the control group for comparison. The IMU sensors were attached to each subject while performing a 6 m walking test. Sixteen variables extracted from the measured data were divided into 7 GE and 9 TM variables explaining pelvis tilt, oblique, and rotation. (3) Results: The tilt range variables of the trunk movement on the affected and unaffected sides were lower than those of the healthy side; this showed between-group differences in various GE variables. For the healthy and affected sides, 80% of variances were explained with 2 or 3 PCs involving only a few dominant variables; and (4) Conclusions: The difference between each side leg should be considered during the development of a diagnosis method. This research can be utilized to develop functional assessment tools for personalized treatment and to design appropriate training protocols.


Subject(s)
Gait Analysis , Gait Disorders, Neurologic/diagnosis , Hemiplegia/diagnosis , Monitoring, Physiologic/instrumentation , Stroke , Torso , Aged , Biomechanical Phenomena , Female , Humans , Male , Middle Aged , Pelvis , Principal Component Analysis , Stroke/complications , Stroke/diagnosis
20.
Chin J Integr Med ; 26(4): 299-306, 2020 Apr.
Article in English | MEDLINE | ID: mdl-29150789

ABSTRACT

OBJECTIVE: To investigate the changes in radial pulse induced by thermal stresses (TSs). METHODS: Sixty subjects were enrolled. Using an open-label, 2×2 crossover randomization design, both feet of each subject were immersed in 15 °C water for cold stress (CS) and in 40 °C water for heat stress (HS) for 5 min each. Radial pulse, respiration and electrocardiogram (ECG) signals were recorded before, during and immediately after the TSs. RESULTS: The analysis of heart rate variability revealed that CS increased the low-frequency (LF) and high-frequency (HF) components (P <0.05) and that HS reduced the LF and HF components (P <0.01). Both TSs reduced the normalized LF, increased the normalized HF, and reduced the LF/HF ratio. The differences in the ECG signals were more dominant during the TS sessions, but those in the radial pulse signals became more dominant immediately after the TS sessions. CS decreased the pulse depth (P <0.01) and increased the radial augmentation index (P <0.1), and HS increased the pulse pressure (P <0.1) and subendocardial viability ratio (P <0.01). There were no significant differences in pulse rate during the three time sequences of each TS. The respiration rate was increased (P <0.1), and the pulse rate per respiration (P/R ratio) was significantly decreased (P <0.05) with CS. The HF region (10-30 Hz) of the pulse spectral density was suppressed during both TSs. CONCLUSIONS: CS induced vasoconstriction and sympathetic reactions, and HS induced vasodilation and parasympathetic reactions. Based on definitions used in pulse diagnosis, we made the novel discoveries that the pulse became slower (decreased P/R ratio), more floating and tenser under CS and that the HF region of the spectral power decreased significantly under both TSs.


Subject(s)
Blood Pressure , Heart Rate , Heat-Shock Response , Parasympathetic Nervous System/physiology , Respiration , Cross-Over Studies , Electrocardiography , Foot , Humans , Vasodilation/physiology
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