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1.
Front Public Health ; 10: 946097, 2022.
Article in English | MEDLINE | ID: mdl-36091547

ABSTRACT

Purpose: Falls are a major public health problem, especially for older people. This research aimed to provide a direct illustration of fall risks among the homebound older people with dementia in China, and to identify the risk factors associated with it. Methods: In 2020, a questionnaire-based field survey was used to assess 1,042 people aged over 60 years in Ningbo, Eastern China. The Morse Fall Risk Scale's result was employed as the dependent variable, while the basic health problems, living environment difficulties, social support problems, and behavioral awareness issues were utilized as the independent variables; subsequently, chi-squared tests and four multivariate ordinarily ordered logistic regression models were performed. Results: Overall, nine hundred and thirty-one older people with dementia were included in this study (the effective rate was 89.34%), with the majority of them having severe dementia (27.9%). Furthermore, 16.2% had fallen in the past 3 months, and 16.8% were at a high risk of falling. The risk factors for the older people's cognitive function included 80-90 years old, vascular dementia, marital status, and history of falls (P < 0.05); the kinds of chronic diseases, the activities of daily living, living environment, caregiver burden, caregiver knowledge, the Cohen Mansfield Agitation Inventory results, and the Clinical Dementia Rating were the protective factors for the risk of falls in them (P < 0.05). Conclusion: The risk of falling of the Chinese homebound older people with dementia was high. Their caregivers, such as relatives, need to pay attention to these risk factors and perform appropriate measures to prevent falls.


Subject(s)
Activities of Daily Living , Dementia , Accidental Falls/prevention & control , Aged , Aged, 80 and over , Caregivers/psychology , China/epidemiology , Dementia/epidemiology , Dementia/psychology , Humans , Middle Aged
2.
Wounds ; 34(8): E66-E70, 2022 Aug.
Article in English | MEDLINE | ID: mdl-36108245

ABSTRACT

INTRODUCTION: Few studies have been done on the burden of minor injuries on trauma centers. Patients with minor injuries require care in the ED, which diverts staff time and resources from patients with more serious injuries and which can sometimes overwhelm the functioning of even the best trauma facility. OBJECTIVE: This study was conducted to assess the burden of minor trauma and thus emphasize the need to develop further management protocols. METHODS: A retrospective observational study was conducted at a level I trauma center for a period of 1 month (February 14, 2020 through March 14, 2020) to assess the burden of minor injuries at that facility. The study population included all patients who required ED care for minor injuries. Data collected included age, sex, time of presentation, anatomical region involved, and interventions done. RESULTS: Of the 3293 patients, 1255 were triaged as green. Seven hundred ninety-one patients with 849 injuries required ED intervention in the minor operation theater. Of the 791 patients, most were male (84.32%), and 61.4% were aged 21 to 40 years. In decreasing order, the most common modes of injury were road traffic injuries (68.4%), fall (15%), and interpersonal violence (13.8%). Maxillofacial injuries were present in 26.15% of patients, 25.8% of patients presented with injuries to the head and neck, 24% with lower extremity injury, and 21.9% with upper extremity injury. CONCLUSIONS: The burden of minor trauma should be recognized. Knowledge of local trauma epidemiology and injury patterns is essential for trauma centers to function well. It is important that all trauma centers should have dedicated protocols in place and trained personnel to address these minor trauma cases.


Subject(s)
Accidental Falls , Trauma Centers , Female , Humans , Male , Retrospective Studies
3.
Comput Intell Neurosci ; 2022: 9626170, 2022.
Article in English | MEDLINE | ID: mdl-36110908

ABSTRACT

Automated human fall detection is an essential area of research due to its health implications in day-to-day life. Detecting and timely reporting of human falls may lead to saving human life. In this paper, fall detection has been targeted using machine-learning-based approaches from two perspectives regarding data sources, that is, contact-based and noncontact-based sensors. In both of these cases, various methods based on deep learning and machine learning techniques have been attempted, and their performances were compared. The approaches analyze data in fixed time windows and extract features in the time domain or spatial domain which obtain relative information between consecutive data samples. After experimentation, it was found that the proposed noncontact-based sensor techniques outperformed the contact-based sensor techniques by a margin of 1.82%. After this, it was also found that the noncontact-based sensor techniques outperformed the state of the art of noncontact-based sensor results by a margin of 3.15%. To better suit these techniques for real-world applications, embedded board implementation and privacy preservation of subject by using advanced methods such as compressive sensing and feature encoding need to be attempted.


Subject(s)
Accidental Falls , Data Compression , Humans , Machine Learning
4.
BMC Geriatr ; 22(1): 749, 2022 Sep 14.
Article in English | MEDLINE | ID: mdl-36100852

ABSTRACT

BACKGROUND: Anxiety and depressive symptoms are associated with fear of falling and fear of falling-related activity restrictions. However, it remains unknown whether anxiety or depressive symptoms alone could predict fear of falling and activity restrictions in older adults. We sought to determine if anxiety and depressive symptoms alone could be an independent predictor of fear of falling and activity restrictions in community-dwelling older adults. METHODS: This longitudinal analysis used waves 5 (time 1, [T1]) and 6 (time 2, [T2], 1 year from T1) data (N = 6376) from the National Health and Aging Trends Study. The Generalized Anxiety Disorder Scale 2 and Patient Health Questionnaire 2 were used to assess anxiety and depressive symptoms, respectively. Interview questions included demographics, health-related data, and fall worry levels (no fear of falling, fear of falling but no activity restrictions, and activity restrictions). Using multinomial logistic regression models, we examined whether anxiety and depressive symptoms (T1) predicted fear of falling and activity restrictions (T2). RESULTS: In wave 5 (T1, mean age: 78 years, 58.1% female), 10 and 13% of participants reported anxiety and depressive symptoms. About 19% of participants experienced fear of falling but not activity restrictions, and 10% of participants developed activity restrictions in wave 6 (T2), respectively. Participants with anxiety symptoms at T1 had a 1.33 times higher risk of fear of falling (95% CI = 1.02-1.72) and 1.41 times higher risk of activity restrictions (95% CI = 1.04-1.90) at T2. However, having depressive symptoms did not show any significance after adjusting for anxiety symptoms. CONCLUSIONS: Anxiety symptoms seemed to be an independent risk factor for future fear of falling and activity restrictions, while depressive symptoms were not. To prevent future fear of falling and activity restrictions, we should pay special attention to older individuals with anxiety symptoms.


Subject(s)
Accidental Falls , Depression , Accidental Falls/prevention & control , Aged , Anxiety/diagnosis , Anxiety/epidemiology , Anxiety Disorders , Depression/complications , Depression/diagnosis , Depression/epidemiology , Female , Humans , Longitudinal Studies , Male , United States/epidemiology
5.
Clin Interv Aging ; 17: 1343-1351, 2022.
Article in English | MEDLINE | ID: mdl-36105916

ABSTRACT

Purpose: Falls are the leading cause of injury among hospitalized patients, particularly among older patients. We investigated the association between serum phosphate (s-phosphate) levels and the risk of in-hospital falls. Patients and Methods: This retrospective observational cohort study included all patients aged over 50 years who were admitted to Yongin Severance Hospital in South Korea between January 2018 and March 2021. Demographic, anthropometric, and biochemical parameters were recorded on admission. S-phosphate levels were classified into three groups: below normal (<2.8 mg/dL), normal (2.8-4.4 mg/dL), and above normal (≥4.5 mg/dL). The normal group was further stratified into tertiles (2.8-3.2, 3.3-3.7, and 3.8-4.4 mg/dL). The incidence of in-hospital falls was compared between the five groups. Logistic regression analyses were performed to assess the association between s-phosphate levels and the incidence of falls during the hospital stay, with clinical factors included as covariates in the multivariable models. Results: A total of 15,485 patients (female: 52.1%) with a median age of 70.0 years (interquartile range: 60.0-79.0 years) were included in the analysis, of whom 295 (1.9%) experienced a fall during the hospital stay. The incidence of falls was significantly higher among patients with lower s-phosphate levels, and this relationship also applied among patients with s-phosphate levels within the normal range as well. The association between lower s-phosphate levels and increased risk of falls remained significant in the adjusted analyses. Conclusion: A lower s-phosphate level on admission was independently associated with an increased risk of in-hospital falls. Further studies are needed to determine whether the s-phosphate level on admission could improve prediction of the risk of in-hospital falls.


Subject(s)
Accidental Falls , Hospitalization , Aged , Female , Humans , Length of Stay , Middle Aged , Phosphates , Retrospective Studies
6.
J Acquir Immune Defic Syndr ; 91(2): 168-174, 2022 Oct 01.
Article in English | MEDLINE | ID: mdl-36094483

ABSTRACT

BACKGROUND: Older (older than 50 years) persons living with HIV (PWH) are at elevated risk for falls. We explored how well our algorithm for predicting falls in a general population of middle-aged Veterans (age 45-65 years) worked among older PWH who use antiretroviral therapy (ART) and whether model fit improved with inclusion of specific ART classes. METHODS: This analysis included 304,951 six-month person-intervals over a 15-year period (2001-2015) contributed by 26,373 older PWH from the Veterans Aging Cohort Study who were taking ART. Serious falls (those falls warranting a visit to a health care provider) were identified by external cause of injury codes and a machine-learning algorithm applied to radiology reports. Potential predictors included a fall within the past 12 months, demographics, body mass index, Veterans Aging Cohort Study Index 2.0 score, substance use, and measures of multimorbidity and polypharmacy. We assessed discrimination and calibration from application of the original coefficients (model derived from middle-aged Veterans) to older PWH and then reassessed by refitting the model using multivariable logistic regression with generalized estimating equations. We also explored whether model performance improved with indicators of ART classes. RESULTS: With application of the original coefficients, discrimination was good (C-statistic 0.725; 95% CI: 0.719 to 0.730) but calibration was poor. After refitting the model, both discrimination (C-statistic 0.732; 95% CI: 0.727 to 0.734) and calibration were good. Including ART classes did not improve model performance. CONCLUSIONS: After refitting their coefficients, the same variables predicted risk of serious falls among older PWH nearly and they had among middle-aged Veterans.


Subject(s)
HIV Infections , Accidental Falls , Aged , Aged, 80 and over , Aging , Cohort Studies , HIV Infections/complications , HIV Infections/drug therapy , Humans , Middle Aged , Polypharmacy
7.
J Allied Health ; 51(3): 180-188, 2022.
Article in English | MEDLINE | ID: mdl-36100713

ABSTRACT

The current study aimed to investigate the long-term effects of receiving post-amputation physical therapy (PT) on individuals' self-reported functional outcomes and quality of life in middle-aged to older adults with lower limb amputation (LLA). Further, we qualitatively explored the patients' perception and experience of PT post-amputation. We assessed participants' functional outcomes using Short-Form Health Survey, Prosthetic Evaluation Questionnaire-Physical Mobility portion, and Fear of Falling Avoidance Behavior Questionnaire. Furthermore, participants' experience and perception to PT were assessed through in-person interviews guided by the custom Amputation Patient Perception Survey. Functional outcome scores were compared between participants who have (Yes-PT) and have not (No-PT) received PT following their amputations, controlling for age. Perception to PT was qualitatively analyzed. Out of the 70 participants, 56 had received PT (80%) following amputation. Functional outcome scores were not significantly different between Yes-PT and No-PT groups. Among participants in the Yes-PT group, 84% expressed overall positive perception toward their post-amputation PT care. Main positive and negative perceptions were related to outcome/benefits and unfulfilled needs/lack of benefits, respectively. Participants with LLA generally expressed a positive perception of PT. However, no significant long-term benefits were found. We recommend goal-directed intervention with patient engagement to improve care experience.


Subject(s)
Accidental Falls , Quality of Life , Aged , Amputation , Cross-Sectional Studies , Fear , Humans , Lower Extremity/surgery , Middle Aged , Patient Outcome Assessment , Physical Therapy Modalities
8.
J Allied Health ; 51(3): 207-214, 2022.
Article in English | MEDLINE | ID: mdl-36100716

ABSTRACT

AIMS: 1) Can virtual fall risk screens be performed safely? 2) Are older adults able to manage technology to participate in telehealth? 3) Does an algorithm aid in referral appropriate evidence-based (EBP) fall prevention programs? METHODS: An algorithm was piloted using the Zoom platform to screen for falls, to assign to intervention groups, and to guide referral to EBP. Statistical analysis of data included descriptive, parametric, and non-parametric tests. RESULTS: Forty-four participants, aged 55-94 years, were screened. A significant relationship between 30-second chair stand and referral between two programs was found (p<0.05). Spearman correlations revealed statistically significant negative correlation between 30-second chair stand and timed up-and-go (TUG) (r= -0.584; p=0.003). No safety incidents occurred. Ninety-five percent of screened participants managed technology requirements successfully. CONCLUSION: Virtual fall risk screens are feasible and offer clinicians an alternative means to screen and refer older adults for EBP.


Subject(s)
Accidental Falls , Physical Therapy Modalities , Accidental Falls/prevention & control , Aged , Feasibility Studies , Humans , Referral and Consultation
10.
PLoS One ; 17(9): e0271315, 2022.
Article in English | MEDLINE | ID: mdl-36054087

ABSTRACT

While all lower limb prosthesis walkers have a high risk of tripping and/or falling, above knee prosthesis users are reported to fall more frequently. Recognising this, engineers designed microprocessor knees (MPK) to help mitigate these risks, but to what extent these devices reduce this disparity between above and below knee users is unclear. A service review was carried out in a prosthetic limb centre regarding the frequency of trips and falls in the previous four weeks. Data from unilateral, community ambulators were extracted. Ordered logistic regressions were applied to investigate whether MPKs mitigated the increased risk of trips and falls for prosthetic knee users, compared to below knee prosthesis users. Socio-demographics (sex, age), prosthesis (prosthesis type, years of use), health (comorbidities, vision, contralateral limb status, medication), and physical function (use of additional walking aids, activity level) were included as covariates. Of the 315 participants in the analysis, 57.5% reported tripping and 20.3% reported falling. Non-microprocessor prosthetic knee (non-MPK) users were shown to trip significantly more than below knee prosthesis users (OR = 1.96, 95% CI = 1.17-3.28). Other covariates showing a significant association included contralateral limb injuries (OR = 1.91, 95% CI = 1.15-3.18) and using an additional walking aid (OR = 1.99, 95% CI = 1.13-3.50). Non-MPK users were also shown to fall significantly more than below knee prosthesis users (OR = 3.34, 95% CI = 1.73-6.45), with no other covariates showing a significant association. MPK users did not show an increased frequency of trips (OR = 0.74, 95% CI = 0.33-1.64) or falls (OR = 0.34, 95% CI = 0.18-2.62), compared to below knee prosthesis users. Of those who tripped at least once in the previous four weeks, those using a non-MPK (OR = 2.73, 95% CI = 1.30-5.74) presented an increased frequency of falling. These findings provide evidence to suggest that the use of MPKs reduces the difference in falls risk between above knee and below knee prosthesis users, providing justification for their provision.


Subject(s)
Amputees , Artificial Limbs , Knee Prosthesis , Accidental Falls/prevention & control , Humans , Microcomputers , Prosthesis Design , Walking
11.
Article in English | MEDLINE | ID: mdl-36078500

ABSTRACT

Maintaining function in older adults is key to the quality of life and longevity. This study examined the potential impact of falls on accelerating further deterioration over time in gait, balance, physical activity, depression, fear of falling, and motor capacity in older adults. 163 ambulatory older adults (age = 76.5 ± 7.7 years) participated and were followed for 6 months. They were classified into fallers or non-fallers based on a history of falling within the past year. At baseline and 6 months, all participants were objectively assessed for gait, balance, and physical activity using wearable sensors. Additional assessments included psychosocial concerns (depression and fear of falling) and motor capacity (Timed Up and Go test). The fallers showed lower gait performance, less physical activity, lower depression level, higher fear of falling, and less motor capacity than non-fallers at baseline and 6-month follow-up. Results also revealed acceleration in physical activity and motor capacity decline compared to non-fallers at a 6-month follow-up. Our findings suggest that falls would accelerate deterioration in both physical activity and motor performance and highlight the need for effective therapy to reduce the consequences of falls in older adults.


Subject(s)
Accidental Falls , Fear , Accidental Falls/prevention & control , Aged , Aged, 80 and over , Depression , Exercise , Fear/psychology , Follow-Up Studies , Gait , Humans , Postural Balance , Quality of Life , Time and Motion Studies
12.
BMC Musculoskelet Disord ; 23(1): 844, 2022 Sep 05.
Article in English | MEDLINE | ID: mdl-36064383

ABSTRACT

BACKGROUND: Falls in older adults are a significant and growing public health concern. There are multiple risk factors associated with falls that may be addressed within the scope of chiropractic training and licensure. Few attempts have been made to summarize existing evidence on multimodal chiropractic care and fall risk mitigation. Therefore, the broad purpose of this review was to summarize this research to date. BODY: Systematic review was conducted following PRISMA guidelines. Databases searched included PubMed, Embase, Cochrane Library, PEDro, and Index of Chiropractic Literature. Eligible study designs included randomized controlled trials (RCT), prospective non-randomized controlled, observational, and cross-over studies in which multimodal chiropractic care was the primary intervention and changes in gait, balance and/or falls were outcomes. Risk of bias was also assessed using the 8-item Cochrane Collaboration Tool. The original search yielded 889 articles; 21 met final eligibility including 10 RCTs. One study directly measured the frequency of falls (underpowered secondary outcome) while most studies assessed short-term measurements of gait and balance. The overall methodological quality of identified studies and findings were mixed, limiting interpretation regarding the potential impact of chiropractic care on fall risk to qualitative synthesis. CONCLUSION: Little high-quality research has been published to inform how multimodal chiropractic care can best address and positively influence fall prevention. We propose strategies for building an evidence base to inform the role of multimodal chiropractic care in fall prevention and outline recommendations for future research to fill current evidence gaps.


Subject(s)
Chiropractic , Accidental Falls/prevention & control , Aged , Gait , Humans
13.
Front Public Health ; 10: 984199, 2022.
Article in English | MEDLINE | ID: mdl-36072374

ABSTRACT

Objective: To examine the risk factors for falls in elderly patients with visual impairment (VI) and assess the predictive performance of these factors. Methods: Between January 2019 and March 2021, a total of 251 elderly patients aged 65-92 years with VI were enrolled and then prospectively followed up for 12 months to evaluate outcomes of accidental falls via telephone interviews. Information of demographics and lifestyle, gait and balance deficits, and ophthalmic and systemic conditions were collected during baseline visits. Forward stepwise multivariable logistic regression analysis was performed to identify independent risk factors of falls in elderly patients with VI, and a derived nomogram was constructed. Results: A total of 143 falls were reported in 251 elderly patients during follow-up, with an incidence of 56.97%. The risk factors for falls in elderly patients with VI identified by multivariable logistic regression were women [odds ratio (OR), 95% confidence interval (CI): 2.71, 1.40-5.27], smoking (3.57, 1.34-9.48), outdoor activities/3 months (1.31, 1.08-1.59), waking up frequently during the night (2.08, 1.15-3.79), disorders of balance and gait (2.60, 1.29-5.24), glaucoma (3.12, 1.15-8.44), other retinal degenerations (3.31, 1.16-9.43) and best-corrected visual acuity (BCVA) of the better eye (1.79, 1.10-2.91). A nomogram was developed based on the abovementioned multivariate analysis results. The area under receiver operating characteristic curve of the predictive model was 0.779. Conclusions: Gender, smoking, outdoor activities, waking up at night, disorders of balance and gait, glaucoma, other retinal degeneration and BCVA of the better eye were independent risk factors for falls in elderly patients with VI. The predictive model and derived nomogram achieved a satisfying prediction of fall risk in these individuals.


Subject(s)
Accidental Falls , Glaucoma , Aged , Female , Humans , Incidence , Male , Risk Factors , Vision Disorders/epidemiology
14.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 1502-1505, 2022 Jul.
Article in English | MEDLINE | ID: mdl-36085756

ABSTRACT

A preliminary study result predicting fall events in patients with Parkinson's disease (PD) by using a simple motion sensor is described in this paper. Causes of falls in people with PD can be postural instability, freezing of gait, festinating gait, dyskinesias, visuospatial dysfunction, orthostatic hypotension, and posture problems. This study uses only one motion sensor in collecting data. Thus, only fall events caused by festinating gait factors, which are moments when the patient suddenly moves faster with smaller steps, can be performed and tested. In this preliminary study, fall event scenarios of simulated test cases are performed by five healthy young subjects aged 20 to 28 years old. The acceleration mode in the motion sensor provides information that can detect how fast the subjects move. Data collected by the sensor will be analyzed by simple analysis methods and machine learning techniques classification. The proposed study achieved an accuracy of 70.3% for the 10-class model, while for binary classification, the accuracy was 99%. Clinical Relevance-This study focuses on predicting falls by analyzing the gaits prior to an actual so that fall prediction can be possible. If falls can be predicted, researchers can develop other protective gear to prevent fall-related injuries not only for PD patients but also for the elderly.


Subject(s)
Dyskinesias , Gait Disorders, Neurologic , Parkinson Disease , Accidental Falls/prevention & control , Adult , Aged , Gait , Humans , Parkinson Disease/complications , Parkinson Disease/diagnosis , Young Adult
15.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 4205-4209, 2022 Jul.
Article in English | MEDLINE | ID: mdl-36085845

ABSTRACT

With the increasing global aging population, the health of the elderly has become a global concern. Accidental falls, as one of the major causes of health and safety issues affecting the elderly, can cause serious hazards. In this paper, a fall detection system is proposed to be able to deliver timely information after a fall. The acceleration and angular velocity time series extracted from motion were used to describe human motion features. Hybrid threshold analysis algorithm and machine learning algorithm are used for classification between falls and activities of daily living (ADLs). The fall detection results showed 98.55% accuracy, 98.16% sensitivity, and 98.73% specificity. The result is higher than the single-threshold algorithm and slightly lower than the machine learning algorithm. In addition, the hybrid algorithm of fall detection in this paper is to put the threshold analysis algorithm in the edge device for calculation and put the machine learning algorithm in the cloud server for calculation. Since the single machine learning algorithm needs to transmit data to the cloud server all the time, the hybrid algorithm has lower power consumption than machine learning algorithms, and the average alarm time is shorter, making it more suitable for actual systems.


Subject(s)
Accidental Falls , Monitoring, Ambulatory , Accidental Falls/prevention & control , Activities of Daily Living , Aged , Algorithms , Humans , Machine Learning
16.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 95-98, 2022 Jul.
Article in English | MEDLINE | ID: mdl-36085891

ABSTRACT

Gait disturbances with falls are common among patients with Parkinson's disease. Falls commonly occur from slips while walking on pathways with turns. Gait phases namely Loading Response and Terminal Stance are linked with forward and backward slips. Also, postural deformities (connected with knee joint angles) are debilitating symptoms of Parkinson's patients and are related with falls. Here, we have focused on exploring the contribution of Loading Response and Terminal Stance to risk of fall along with the relevance of postural deformity (e.g., knee bending) while an individual walked overground on pathways (with 0° and 180° turn) under dual task condition. For this, we have used a wearable device consisting of a pair of Sensored shoes and Knee Bending Angle Recorder Units. The device was used to compute Coefficient of Variation of knee bending angle during different gait phases as an indicator of one's risk of fall that corroborated with clinical measure. Clinical Relevance- A study with age and gender matched healthy and Parkinson's individuals indicated the importance of Loading Response and pathway turn while assessing risk of fall. This can serve as important pre-clinical input while designing intervention paradigms.


Subject(s)
Parkinson Disease , Wearable Electronic Devices , Accidental Falls/prevention & control , Gait/physiology , Humans , Knee Joint , Parkinson Disease/diagnosis
17.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 4683-4686, 2022 Jul.
Article in English | MEDLINE | ID: mdl-36086537

ABSTRACT

Falls associated injuries often result not only increasing the medical-, social- and care-cost but also loss of mobility, impair chronic health and even potential risk of fatality. Because of elderly population growth, it is one of the major global public health problems. To address such issue, we present a Deep Learning enabled Fall Detection (DLFD) method exploiting Gait Analysis. More in details, firstly, we propose a framework for fall detection system. Secondly, we discussed the proposed DLFD method which exploits fall and non-fall RGB video to extract gait features using MediaPipe framework, applies normalization algorithm and classifies using bi-directional Long Short-Term Memory (bi-LSTM) model. Finally, the model is tested on collected three public datasets of 434x2 videos(more than 1 million frames) which consists of different activities and varieties of falls. The experimental results show that the model can achieve the accuracy of 96.35% and reveals the effectiveness of the proposal. This could play a significant role to alleviate falls problem by immediate alerting to emergency and relevant teams for taking necessary actions. This will speed up the assistance proceedings, reduce the risk of prolonged injury and save lives.


Subject(s)
Deep Learning , Gait Analysis , Accidental Falls/prevention & control , Aged , Algorithms , Gait , Humans
18.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 2390-2394, 2022 Jul.
Article in English | MEDLINE | ID: mdl-36086546

ABSTRACT

One of the consequences of aging is the increased risk of falls, especially when someone walks in unknown or uncontrolled environments. Usually, gait is evaluated through observation and clinical assessment scales to identify the state and deterioration of the patient's postural control. Lately, technological systems for bio-mechanical analysis have been used to determine abnormal gait states being expensive, difficult to use, and impossible to apply in real conditions. In this article, we explore the ability of a system based on a single inertial measurement unit located in the lower back to estimate spatio-temporal gait parameters by analyzing the signals available in the Physionet repository "Long Term Movement Monitoring Database" which, together with automatic classification algorithms, allow predicting the risk of falls in the elderly population. Different classification algorithms were trained and evaluated, being the Support Vector Machine classifier with a third-degree polynomial kernel, cost function C = 2 with the best performance, with an Accuracy = 59%, Recall = 91%, and F1- score = 71%, providing promising results regarding a proposal for the quantitative, online and realistic evaluation of gait during activities of daily living, which is where falls actually occur in the target population. Clinical Relevance - This work proposes an early risk of falls detection tool, essential to start preventive treatment strategies to maintain the independence of the elderly through a non-invasive, simple, and low-cost alternative.


Subject(s)
Accidental Falls , Activities of Daily Living , Accidental Falls/prevention & control , Aged , Gait , Humans , Postural Balance , Walking
19.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 3640-3644, 2022 Jul.
Article in English | MEDLINE | ID: mdl-36086565

ABSTRACT

Human gait is a complex system affected by many other processes of human physiology. It has multiple inputs and multiple outputs. Due to its complex nature, signals obtained from this system also exhibit complexity and variability. It has been analyzed in many ways to extract the information inhabited by these signals. Entropy based methods showed a significant impact on analysis of gait signals. Threshold based symbolic entropy analysis is one of the entropy based method applied to human gait signals. In this method Normalized Corrected Shannon Entropy (NCSE) is calculated to compare the spontaneous output of the human locomotors system during different walking conditions. Selection of the threshold values is an important task and sometimes it depends upon the type and size of the data. Results are dependent on the proper selection of the threshold. In this paper, different threshold selection methods are discussed and their impact on the results are presented. It was observed that, variation in stride interval has performed better as a threshold value as compare to the other methods. It provided maximum separation among different groups of gait data used in this study. We concluded with the recommendations for the proper selection of the threshold values to apply symbolic entropy methods on human gait signals. Clinical relevance Various gait related problems are common in older adults that increase with age and are associated with reduced gait speed increased fall risk and other impairments. Consequently objective gait assessment in the clinics depending upon the size of the available data has become increasingly important for the classification of gait. It was found that while applying symbolic entropy method proper selection of threshold result into improved classification of different types of gait data which will help the clinician for better decision-making regarding treatment.


Subject(s)
Gait , Walking , Accidental Falls , Aged , Entropy , Gait/physiology , Humans , Walking/physiology , Walking Speed/physiology
20.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 2421-2425, 2022 Jul.
Article in English | MEDLINE | ID: mdl-36086625

ABSTRACT

Most elderly patients after falling, being not able to rise up or call for help, are particularly at risk of complication. This urges for the development of autonomous devices for earliest detection of falls. This paper is an overview of the current design approaches to autonomous fall detectors - sensors and algorithms- and a methodology to assess their efficiency. We then propose our fall sensor, which features high sensitivity (95%) and specificity (99%) on simulated falls in lab settings, and lower sensitivity (62.5%) in real settings in a group of 10 patients, with 8 falls detected over a period of 28 days.


Subject(s)
Accidental Falls , Monitoring, Ambulatory , Accidental Falls/prevention & control , Aged , Algorithms , Humans
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