RESUMO
[Purpose] The purpose of this study was to verify whether Timed Up and Go (TUG) test measurements differed according to the seat height of the chair, presence or absence of armrests, and measurement location in young healthy adults, and to clarify the flexibility of the TUG settings. [Participants and Methods] Fifty-nine young healthy males and females participated in this study. The TUG test was performed under several conditions. Eight measurements were obtained at both the usual walking speed and the individual's fastest walking speed. [Results] There were no significant differences in TUG test measurements according to variation in seat height, different measurement locations, with and without the use of armrests, or at the usual walking speed or the fastest walking speed. [Conclusion] In young healthy adults, TUG test measurements were unaffected by differences in chair height, use of armrests, or the location of the measurement. If TUG measurements are found to differ according to these variables, it is necessary to consider the influence of the individual's ability rather than the measurement method.
RESUMO
PURPOSE: The aim of this study was to investigate and improve the accuracy of accelerometer-type pedometers used by the elderly with slow walking speeds, with or without gait disorders, who do or do not use a cane. METHODS: Eighteen subjects walked with a cane (5 males, 13 females; age, 80.9 +/- 7.7 yr; height, 148.1 +/- 7.7 cm; weight, 51.8 +/- 8.8 kg (mean +/- SD); nine had impaired gait), and 31 subjects walked without a cane (7 males, 24 females; age, 80.9 +/- 7.7 yr; height, 148.1 +/- 7.7 cm; weight, 51.8 +/- 8.8 kg; 15 had impaired gait). Subjects walked for approximately 20 m (10 m in each direction and a turning arc) at their own speed. We determined the number of steps by pedometer (PM), by visually counting the actual number of steps (RM), and by the triaxial acceleration signals. The power spectrum of the accelerometer in each direction calculated by fast Fourier transform (FFT) for a 4-s temporal window was normalized with the maximum power of each window. It was composited, and the frequency at maximum power was considered as the cadence. The number of steps taken (FM) was determined by summing all the estimated steps in each window. RESULTS: PM was significantly less than the RM (P < 0.05), and the error of PM was 53.2 +/- 34.1% of RM. FM did not differ from the RM, and the average error of FM was -0.7 +/- 7.9% of RM (absolute value: 5.8 +/- 5.3%). CONCLUSION: We suggest that our FFT method is suitable for estimating the number of steps during walking in this population.
Assuntos
Aceleração , Teste de Esforço/métodos , Análise de Fourier , Monitorização Ambulatorial/métodos , Caminhada/fisiologia , Idoso , Idoso de 80 Anos ou mais , Feminino , Transtornos Neurológicos da Marcha , Humanos , Masculino , Análise Numérica Assistida por ComputadorRESUMO
We examined falling risk among elderly using a wearable inertial sensor, which combines accelerometer and gyrosensors devices, applied during the Timed Up and Go (TUG) test. Subjects were categorised into two groups as low fall risk and high fall risk with 13.5 s duration taken to complete the TUG test as the threshold between them. One sensor was attached at the subject's waist dorsally, while acceleration and gyrosensor signals in three directions were extracted during the test. The analysis was carried out in phases: sit-bend, bend-stand, walking, turning, stand-bend and bend-sit. Comparisons between the two groups showed that time parameters along with root mean square (RMS) value, amplitude and other parameters could reveal the activities in each phase. Classification using RMS value of angular velocity parameters for sit-stand phase, RMS value of acceleration for walking phase and amplitude of angular velocity signal for turning phase along with time parameters suggests that this is an improved method in evaluating fall risk, which promises benefits in terms of improvement of elderly quality of life.
Assuntos
Acidentes por Quedas/prevenção & controle , Fisiologia/métodos , Medição de Risco , Idoso , Fenômenos Biomecânicos , Feminino , Marcha , Humanos , Masculino , Qualidade de Vida , Processamento de Sinais Assistido por Computador , Fatores de Tempo , CaminhadaRESUMO
We performed a quantitative analysis of the fall-risk assessment test using a wearable inertia sensor focusing on two tests: the time up and go (TUG) test and the four square step test (FSST). These tests consist of various daily activities, such as sitting, standing, walking, stepping, and turning. The TUG test was performed by subjects at low and high fall risk, while FSST was performed by healthy elderly and hemiplegic patients with high fall risk. In general, the total performance time of activities was evaluated. Clinically, it is important to evaluate each activity for further training and management. The wearable sensor consisted of an accelerometer and angular velocity sensor. The angular velocity and angle of pitch direction were used for TUG evaluation, and those in the pitch and yaw directions at the thigh were used for FSST. Using the threshold of the angular velocity signal, we classified the phase corresponding to each activity. We then observed the characteristics of each activity and recommended suitable training and management. The wearable sensor can be used for more detailed evaluation in fall risk management. The wearable sensor can be used more detailed evaluation for fall-risk management test.
Assuntos
Acidentes por Quedas/prevenção & controle , Teste de Esforço/métodos , Monitorização Ambulatorial/métodos , Medição de Risco/métodos , Caminhada/fisiologia , Aceleração , Idoso , Fenômenos Biomecânicos , Desenho de Equipamento , Voluntários Saudáveis , Hemiplegia/fisiopatologia , Humanos , Pessoa de Meia-Idade , Movimento (Física) , Pacientes Ambulatoriais , Acidente Vascular Cerebral/fisiopatologiaRESUMO
Daily monitoring of health condition is important for an effective scheme for early diagnosis, treatment and prevention of lifestyle-related diseases such as adiposis, diabetes, cardiovascular diseases and other diseases. Commercially available devices for health care monitoring at home are cumbersome in terms of self-attachment of biological sensors and self-operation of the devices. From this viewpoint, we have been developing a non-conscious physiological monitor installed in a bath, a lavatory, and a bed for home health care and evaluated its measurement accuracy by simultaneous recordings of a biological sensors directly attached to the body surface. In order to investigate its applicability to health condition monitoring, we have further developed a new monitoring system which can automatically monitor and store the health condition data. In this study, by evaluation on 3 patients with cardiac infarct or sleep apnea syndrome, patients' health condition such as body and excretion weight in the toilet and apnea and hypopnea during sleeping were successfully monitored, indicating that the system appears useful for monitoring the health condition during daily living.
Assuntos
Automação , Serviços de Assistência Domiciliar , Monitorização Ambulatorial/instrumentação , Infarto do Miocárdio/fisiopatologia , Síndromes da Apneia do Sono/fisiopatologia , Telemetria/instrumentação , Atividades Cotidianas , Processamento Eletrônico de Dados , Desenho de Equipamento , Arquitetura de Instituições de Saúde , Humanos , Monitorização Ambulatorial/métodos , Infarto do Miocárdio/diagnóstico , Processamento de Sinais Assistido por Computador/instrumentação , Síndromes da Apneia do Sono/diagnóstico , Telemedicina/instrumentação , Telemedicina/métodos , Telemetria/métodos , Banheiros , TransdutoresRESUMO
In this study, we evaluated the influence of floor materials on standing and walking in hemiplegic patients. To monitor body motion during standing and walking without any constraint, we used a measurement system that consisted of an accelerometer device, a telemeter system, and a personal computer. The posture angles in the antero-posterior and lateral directions were calculated from the low frequency component of the acceleration signal to evaluate body motion. Experiments were performed with six poststroke hemiplegic patients. We modified the time up and go test introduced by Podsiadle. The patients executed the task on three different floor materials: wooden flooring, linoleum, and carpet. The posture angle pattern on carpet differed from those on wooden flooring and linoleum. Therefore, the floor material influenced body motion. We suspect that this difference in movement corresponds to the hardness of the material.