Overview

The Walker Fall Detection Data Set is a curated compilation of inertial data designed for the study of fall detection systems, specifically for people using walking assistance. This data set offers deep insight into various movement patterns. It covers data from four different classes: idle, motion, step and fall.

This dataset was published as part of a research paper: Dataset and System Design for Orthopedic Walker Fall Detection and Activity Logging Using Motion Classification

Data Acquisition

Data was recorded using an IMU affixed to a walker, as illustrated in the image below:

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15943143%2F134aaf57e284d20775d37ecdfa14d30e%2F20230712_163957.jpg?generation=1695049359163422&alt=media" alt="Walker">

The IMU used for this project is the Arduino Nano 33 BLE Sense. It's powered by a LiPo battery and is equipped with a voltage regulator and a dedicated battery charging circuit. To ensure durability and protection during the data recording phase, the entire prototype was securely housed in a custom 3D-printed casing.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15943143%2F0c8458d7bd161e983e1676e72d89085d%2F20230712_163957_2.jpg?generation=1695050869941377&alt=media" alt="">

The prototype was designed to transmit data wirelessly to a computer using Bluetooth Low Energy (BLE). Upon receipt, a Python script processed the incoming data and stored it in JSON format. The data transmission rate was optimized to achieve the highest possible rate, resulting in approximately 100 samples per second, covering both accelerometer and gyroscope data.

Data were collected from four different subjects, each of whom maneuvered the walker down a hallway, primarily capturing step and movement data. It is important to note that the “**idle**” data are not subject-specific, as it represents periods in which the walker is stationary. Similarly, “**fall**” data is also not linked to any particular individual; was obtained by deliberately pushing the walker from a vertical position to the ground.

Data Processing

This dataset contains four classes:

• Idle: Represents periods of no movement, indicating that the walker is stationary.
• Step: Capture moments when an individual takes a step using the walker.
• Movement: Covers any movement that is not considered a step or a fall, such as when carrying the walker or adjusting its position.
• Fall: Denotes cases in which the walker tips over and falls to the ground from an upright position.

To effectively categorize the data, several processing steps were executed. Initially, the data was reduced from its original 100 samples per second to ensure a constant time step between samples, since the original rate was not uniformly constant. After this, both the acceleration and gyro data were normalized to one sample every 12.5 milliseconds, resulting in a rate of 80 samples per second. This normalization allowed the synchronization of acceleration and gyroscope data, which were subsequently stored in dictionaries in JSON format. Each dictionary contains the six dimensions (three acceleration and three gyro) corresponding to a specific timestamp.

To distinguish individual samples within each group, the root mean square (RMS) value of the six dimensions (comprising acceleration and gyroscope data) was calculated. Subsequently, an algorithm based on the hidden Markov model (HMM) was used to discern the hidden states inherent in the data, which facilitated the segmentation of the data set.

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Through the filtering process, the HMM effectively identifies individual steps. Once all steps were identified, the window size was determined based on the duration of each step. A window size of 160 samples was chosen, which, given a rate of 80 samples per second, is equivalent to a duration of 2 seconds for each sample.

A similar procedure is employed to extract "fall" samples. However, for "idle" and "motion" samples, isolation isn't necessary. Instead, samples from these categories can be arbitrarily chosen from the recorded clusters.

Final Dataset The finalized dataset is presented in CSV format. The first column serves as the label column and covers all four classes. In addition to this, the CSV file has 960 columns of functions. These columns encapsulate 160 samples each of acceleration and gyro data in the x, y, and z axes.

Each class contains 620 samples, bringing the overall total to 2480 samples across all classes.

Citation and Use

This dataset is associated with a research article currently un...

This is historical data. The update frequency has been set to "Static Data" and is here for historic value. Updated on 8/14/2024

Fall-Related Death Rate - This indicator shows the rate of fall-related deaths per 100,000 population. Falls are a major cause of preventable death among the elderly and have increased across age groups in the past decade. Causes of fall-related deaths differ between the elderly and young and middle-aged populations, and require different prevention strategies. In 2009, falls accounted for 30% of accidental deaths. Link to Data Details

This dataset is about book subjects. It has 3 rows and is filtered where the books is The falling rate of profit in the postwar United States economy. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

30 Year Mortgage Rate in the United States decreased to 6.77 percent in June 26 from 6.81 percent in the previous week. This dataset includes a chart with historical data for the United States 30 Year Mortgage Rate.

The benchmark interest rate in the United States was last recorded at 4.50 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Fixed 30-year mortgage rates in the United States averaged 6.88 percent in the week ending June 20 of 2025. This dataset provides the latest reported value for - United States MBA 30-Yr Mortgage Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

About this dataset

Context

The dataset tabulates the data for the Falling Spring, WV population pyramid, which represents the Falling Spring population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Falling Spring, WV, is 16.9.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Falling Spring, WV, is 49.4.
• Total dependency ratio for Falling Spring, WV is 66.3.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Falling Spring, WV is 2.0.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Falling Spring population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Falling Spring for the selected age group is shown in the following column.
• Population (Female): The female population in the Falling Spring for the selected age group is shown in the following column.
• Total Population: The total population of the Falling Spring for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Falling Spring Population by Age. You can refer the same here

Household Saving Rate in the United States decreased to 4.50 percent in May from 4.90 percent in April of 2025. This dataset provides - United States Personal Savings Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Decrease the rate of unintentional fall-related injury fatalities of older adults from 80.1 per 100,000 in 2013 to 68.1 per 100,000 by 2017.

Open AccessSupplementary Data A shows meta-data for in-situ and laboratory measurements of soil respiration or its components soil heterotrophic respiration and autotrophic respiration, as well as associated environmental variables from global pristine peatlands and water table decline peatlands, respectively. Supplementary Data B shows the relationships between peatland subsidence rates and drainage years for different land uses in different climate zones, relationships between proportion of peatland subsidence rates due to oxidation and drainage years for different land uses in different climate zones, the estimated peat subsidence rates and peat subsidence rates due to oxidation, the synthesized soil organic carbon content and soil bulk density at the layer of 0-30 cm from pristine peatlands, and the in-situ measured annual soil heterotrophic respiration rates for validating the robustness of the developed emipirical models of this study.

About this dataset

Context

The dataset tabulates the Falling Spring population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Falling Spring across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Falling Spring was 169, a 0% decrease year-by-year from 2022. Previously, in 2022, Falling Spring population was 169, a decline of 1.17% compared to a population of 171 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Falling Spring decreased by 38. In this period, the peak population was 212 in the year 2011. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Falling Spring is shown in this column.
• Year on Year Change: This column displays the change in Falling Spring population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Falling Spring Population by Year. You can refer the same here

Dropout rates for Alaska public school districts. The dropout rate is defined by state regulation 4 AAC 06.895(i)(3) as a fraction of students grades 7-12 who have dropped out during the current school year out of the total students in grades 7-12 enrolled as of October 1st of the school year for which the data is reported.A student is considered to be a dropout when they have discontinued schooling for a reason other than graduation, transfer to another diploma-track program, emigration, or death unless the student is enrolled and in attendance at the same school or at another diploma-track program prior to the end of the school year (June 30).Students who depart a diploma track program in pursuit of GED certification, credit recovery, or non-diploma track vocational training are considered to have dropped out.This data set includes historic data from 1991 to present.GIS layers for individual years can be accessed using the Build Your Own Map application.Source: Alaska Department of Education & Early Development

This data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: Alaska Department of Education & Early Development Data Center

The benchmark interest rate in Pakistan was last recorded at 11 percent. This dataset provides - Pakistan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset tabulates the Fall River population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Fall River across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Fall River was 93,840, a 0.22% increase year-by-year from 2022. Previously, in 2022, Fall River population was 93,636, a decline of 0.32% compared to a population of 93,936 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Fall River increased by 1,769. In this period, the peak population was 93,940 in the year 2020. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Fall River is shown in this column.
• Year on Year Change: This column displays the change in Fall River population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Fall River Population by Year. You can refer the same here

Inflation Rate in the United States increased to 2.40 percent in May from 2.30 percent in April of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset tracks the updates made on the dataset "SHIP Fall-Related Death Rate 2009-2021" as a repository for previous versions of the data and metadata.

The benchmark interest rate In the Euro Area was last recorded at 2.15 percent. This dataset provides - Euro Area Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Data from: Drivers of snag fall rates in Fennoscandian boreal forests

https://doi.org/10.5061/dryad.37pvmcvtt

Data used for fitting the models in Aakala et al. (2024). Drivers of snag fall rates in Fennoscandian boreal forests to be published in Journal of Applied Ecology.

Description of the data and file structure

The tab-separated text file contains variables used in modeling the probability of standing dead trees to remain standing over the 5-year remeasurement interval. The variables (with full descriptions in the main article):

survival = binary response variable, whether the standing dead tree survived as standing (1), or fell (0).

dbh = Diameter at 1.3 m height, in cm.

gdd0 = Growing degree days, with a threshold value of 0 °C. Originally obtained from the Envirem data set (Title, P.O. and Bemmels, J.B., 2018. ENVIREM: an expanded set of bioclimatic and topographic variables increases flexibility and improves performance of e...

This U.S. Army Corps of Engineers (USACE)-funded study that began in 2005 compares the SARs of PIT tagged juvenile hatchery Snake River fall Chinook that are split into two groups, released above Lower Granite Dam, and when detected at downstream dams, one group is transported (if detected) and the other group bypassed if detected. When adult returns are complete, their SARs will be compared to determine the efficacy of smolt transport of this stock. Scales are collected on returning adults to determine age at ocean entry. The study is a collaborative effort with the U.S. Fish and Wildlife Service (USFWS), Washington Dept. of Fish and Wildlife (WDFW), and the Nez Perce Tribe (NPT). Juvenile releases began in 2005, and will be completed in 2012. Adult returns will be completed in 2016, with a final report provided to the USACE and region summarizing study results. Fall Chinook transport study data.

The benchmark interest rate in India was last recorded at 5.50 percent. This dataset provides - India Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.