Background: The anterior-posterior ground reaction force (AP-GRF) and propulsion and braking point metrics derived from the AP-GRF time series are indicators of locomotor function across healthy and neurological diagnostic groups. In this paper, we describe the use of a minimal set of wearable inertial measurement units (IMUs) to indirectly measure the AP-GRFs generated during healthy and hemiparetic walking. Methods: Ten healthy individuals and five individuals with chronic post-stroke hemiparesis completed a 6-minute walk test over a walking track instrumented with six forceplates while wearing three IMUs securely attached to the pelvis, thigh, and shank. Subject-specific models driven by IMU-measured thigh and shank angles and an estimate of body acceleration provided by the pelvis IMU were used to generate indirect estimates of the AP-GRF time series. Propulsion and braking point metrics (i.e., peaks, peak timings, and impulses) were extracted from the IMU-generated time series. Peaks and impulses were expressed as % bodyweight (%bw) and peak timing was expressed as % stance phase (%sp). A 75%-25% split of 6-minute walk test data was used to train and validate the models. Indirect estimates of the AP-GRF time series and point metrics were compared to direct measurements made by the forceplates. Results: Indirect measurements of the AP-GRF time series approximated the direct measurements made by forceplates, with low error and high consistency in both the healthy (RMSE = 4.5%bw; R 2 = 0.93) and post-stroke (RMSE = 2.64%bw; R 2 = 0.90) cohorts. In the healthy cohort, the average errors between indirect and direct measurements of the peak propulsion magnitude, peak propulsion timing, and propulsion impulse point estimates were 2.37%bw, 0.67%sp, and 0.43%bw. In the post-stroke cohort, the average errors for these point estimates were 1.07%bw, 1.27%sp, and 0.31%bw. Average errors for the braking estimates were higher, but comparable. Conclusions: Accurate estimates of AP-GRF metrics can be generated using three strategically mounted IMUs and subject-specific calibrations. This study advances the development of point-of-care diagnostic systems that can catalyze the routine assessment and management of propulsion and braking locomotor deficits during rehabilitation.

Abstract Background: The anterior-posterior ground reaction force (AP-GRF) and propulsion and braking metrics derived from the AP-GRF time series are indicators of locomotor function across healthy and neurological diagnostic groups. In this paper, we describe the use of a minimal set of wearable inertial measurement units (IMUs) to indirectly measure the AP-GRFs generated during healthy and hemiparetic walking. Methods: Ten healthy individuals and five individuals with chronic post-stroke hemiparesis completed a 6-minute walk test over a walking track instrumented with six forceplates while wearing three IMUs securely attached to the pelvis, thigh, and shank. Subject-specific models driven by IMU-measured thigh and shank angles and an estimate of body acceleration provided by the pelvis IMU were used to generate indirect estimates of the AP-GRF time series. Propulsion and braking point metrics (i.e., peaks, peak timings, and impulses) were extracted from the IMU-generated time series. Peaks and impulses were expressed as % bodyweight (%bw) and peak timing was expressed as % stance phase (%sp). A 75%-25% split of 6-minute walk test data was used to train and validate the models. Indirect estimates of the AP-GRF time series and point metrics were compared to direct measurements of the same made by the reference standard forceplates. Results: Indirect measurements of the AP-GRF time series strongly approximated the direct measurements made by forceplates, with low error and high consistency in both the healthy (RMSE = 4.5 %bw; R2 = 0.93) and post-stroke (RMSE = 2.65 %bw; R2 = 0.90) cohorts. In the healthy cohort, the average errors between indirect and direct measurements of the peak propulsion magnitude, peak propulsion timing, and propulsion impulse point estimates were 2.37 %bw, 0.67 %sp, and 0.43 %bw. In the post-stroke cohort, the average errors for these same point estimates were 1.07 %bw, 1.27 %sp, and 0.31 %bw. Average errors for the braking-related point estimates were higher, but comparable. Conclusions: Accurate estimates of the AP-GRF time series and key propulsion and braking point metrics can be generated using three strategically mounted IMUs and subject-specific calibrations. This study is a foundational step toward the development of point-of-care diagnostic systems that can catalyze the routine assessment and management of propulsion and braking locomotor deficits during rehabilitation.

Common quibbles in most homes are the temperature setting. Some family members are comfortable with cooler temperature settings, while other family members prefer warmer temperature settings. Not to mention the fragile elderly and some medical situations require different temperature settings for those individuals than the rest of the occupants of the space. The purpose of this article is to outline a research where we created a working prototype of a portable, effective Peltier cooling/heating system. Peltier, or thermoelectric modules, are devices that use the differences in electric voltages to create a difference in temperature between two flat opposite sides of the thin module. The system can easily be switched between the heating and cooling modes. In contrast to compression refrigeration systems it produces a very low level of noise output. Also, the system is portable, small in size, and light weight. Another advantage of using the Peltier system is it does not employ hazardous substances such as hydrochlorofluorocarbons, but uses water. While a system such as this could be beneficial in the day to day comfort of any individual, it could prove vital to the survival of the elderly and medically vulnerable individuals. This heating/cooling system can enhance the performance of military, particularly in biological warfare suites, and law enforcement personnel who find themselves in less than desirable weather conditions. This uniquely designed Peltier system is compact, and lightweight. Cooling/heating through the system would be achieved by the exchange of heat between the user and a custom designed vest. The system is powered by lithium ion battery pack. Details of this unique design are discussed in the article. Also, the testing and results are reported, and discussed.

Abstract Background: The anterior-posterior ground reaction force (AP-GRF) and propulsion and braking metrics derived from the AP-GRF time series are meaningful indicators of locomotor function across healthy and neurological diagnostic groups. In this paper, we describe the use of a minimal set of wearable inertial measurement units (IMUs) to indirectly measure the AP-GRF time series during healthy and hemiparetic walking.Methods: Ten healthy individuals and five individuals with chronic post-stroke hemiparesis completed a 6-minute walk test over a walking track instrumented with six forceplates while wearing three IMUs securely attached to the pelvis, thigh, and shank. Subject-specific models driven by IMU-measured thigh and shank angles and an estimate of body acceleration provided by the pelvis IMU were used to generate indirect estimates of the AP-GRF time series. Propulsion and braking point metrics (i.e., peaks, peak timings, and impulses) were extracted from the IMU-generated time series. A 75%-25% split of 6-minute walk test data was used to train and validate the models. Indirect estimates of the AP-GRF time series and point metrics were compared to direct measurements of the same made by the reference standard forceplates. Results: Indirect measurements of the AP-GRF time series strongly approximated the direct measurements made by forceplates, with low error and high consistency in both the healthy (RMSE = 4.5 %bw; R2 = 0.93) and post-stroke (RMSE = 2.65 %bw; R2 = 0.90) cohorts. In the healthy cohort, the average error between indirect and direct measurements of the magnitude (% bodyweight, %bw) and timing (% stance phase, %sp) of the peak propulsion and braking point metrics was less than 1.8 %bw and 0.8 %sp in the training dataset and less than 2.7 %bw and 1.4 %sp in the validation dataset. Similarly, the average error for the propulsion and braking impulses was less than 0.52 %bw and 0.68 %bw for the training and validation datasets, respectively. In the post-stroke cohort, the average error was less or comparable for every metric. Conclusions: Highly accurate estimates of the AP-GRF time series and key propulsion and braking point metrics can be generated using three strategically mounted IMUs and subject-specific calibrations. This study is a foundational step toward the development of point-of-care diagnostic systems that can catalyze the routine assessment and management of propulsion and braking locomotor deficits during rehabilitation.

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