## Time Series Chart: Activity Signal Data ### Overview The image is a time series chart displaying signal data across three axes (x, y, z) over a period of time. The chart is annotated with labels indicating different activities performed during the recording period, such as walking, skipping, staying, jogging, and going up or down stairs. The data appears to be sensor data, possibly from an accelerometer or similar device. ### Components/Axes * **X-axis:** "Time", with a scale from 0 to 10000. Axis markers are present at 0, 2000, 4000, 6000, 8000, and 10000. * **Y-axis:** "Signal", with a scale from -2 to 2. Axis markers are present at -2, -1, 0, 1, and 2. * **Data Series:** * **x (blue):** Varies between approximately 0 and 1. * **y (orange):** Varies between approximately -2 and 0. * **z (green):** Varies between approximately -2 and 2. * **Activity Labels:** "walk", "skip", "stay", "jog", "stUp", "stDown" are placed above the chart, indicating the activity being performed during that time interval. These labels are separated by vertical lines. * **Vertical Lines:** Red and blue vertical lines separate the different activity segments. ### Detailed Analysis * **Walk (0-1000):** * x (blue): Oscillates between approximately 0 and 1. * y (orange): Oscillates between approximately -2 and -1. * z (green): Oscillates between approximately -1 and 2. * **Skip (1000-2000):** * x (blue): Oscillates between approximately 0 and 1. * y (orange): Oscillates between approximately -2 and -1. * z (green): Oscillates between approximately -1 and 2. * **Stay (2000-3000):** * x (blue): Remains relatively constant at approximately 0. * y (orange): Remains relatively constant at approximately -1. * z (green): Remains relatively constant at approximately 0.5. * **Jog (3000-4000):** * x (blue): Oscillates between approximately 0 and 1. * y (orange): Oscillates between approximately -2 and -1. * z (green): Oscillates between approximately -1 and 2. * **Walk (4000-5000):** * x (blue): Oscillates between approximately 0 and 1. * y (orange): Oscillates between approximately -2 and -1. * z (green): Oscillates between approximately -1 and 2. * **stUp (5000-6000):** * x (blue): Oscillates between approximately 0 and 1. * y (orange): Oscillates between approximately -2 and -1. * z (green): Oscillates between approximately -1 and 2. * **Stay (6000-7000):** * x (blue): Remains relatively constant at approximately 0. * y (orange): Remains relatively constant at approximately -1. * z (green): Remains relatively constant at approximately 0. * **stDown (7000-8000):** * x (blue): Oscillates between approximately 0 and 1. * y (orange): Oscillates between approximately -2 and -1. * z (green): Oscillates between approximately -1 and 2. * **Walk (8000-9000):** * x (blue): Oscillates between approximately 0 and 1. * y (orange): Oscillates between approximately -2 and -1. * z (green): Oscillates between approximately -1 and 2. * **Stay (9000-10000):** * x (blue): Remains relatively constant at approximately 0. * y (orange): Remains relatively constant at approximately -1. * z (green): Remains relatively constant at approximately 0. * **Jog (10000-):** * x (blue): Oscillates between approximately 0 and 1. * y (orange): Oscillates between approximately -2 and -1. * z (green): Oscillates between approximately -1 and 2. * **Skip (10000-):** * x (blue): Oscillates between approximately 0 and 1. * y (orange): Oscillates between approximately -2 and -1. * z (green): Oscillates between approximately -1 and 2. ### Key Observations * The "stay" activity segments are characterized by relatively constant signal values for all three axes. * The "walk", "skip", "jog", "stUp", and "stDown" activities are characterized by oscillations in all three axes. * The z-axis (green) shows the most significant variation during the active periods. * The y-axis (orange) consistently shows negative values. * The x-axis (blue) consistently shows values around 0. ### Interpretation The chart visualizes sensor data that can be used to differentiate between different human activities. The "stay" activity serves as a baseline, while the other activities generate distinct oscillatory patterns in the signal data. The z-axis appears to be the most sensitive to movement, while the y-axis might be related to gravity or a constant force. The data suggests that it is possible to classify these activities using machine learning techniques based on the patterns observed in the signal data. The consistent patterns within each activity type suggest a degree of repeatability and reliability in the sensor readings.

## Line Chart: Time Series of Sensor Signals During Various Activities ### Overview This image displays a line chart showing the time series of three sensor signals (labeled x, y, and z) recorded over a period of approximately 11,000 time units. The chart is segmented by vertical colored lines and labeled with different human activities, indicating changes in the signal patterns corresponding to these activities. ### Components/Axes * **X-axis**: Labeled "Time", with tick marks at 0, 2000, 4000, 6000, 8000, and 10000. The axis represents the progression of time. * **Y-axis**: Labeled "Signal", with tick marks at -2, -1, 0, 1, and 2. The axis represents the amplitude or magnitude of the sensor signals. * **Legend**: Located in the top-right corner of the chart. It indicates the color mapping for each signal: * Blue line: 'x' * Orange line: 'y' * Green line: 'z' * **Activity Labels**: Text labels are placed above the chart, indicating specific activities at different time intervals. These labels are: "walk", "skip", "stay", "jog", "walk", "stUp", "stay", "stDown", "walk", "stay", "skip", "jog". * **Vertical Dividers**: Colored vertical lines (primarily red and blue) demarcate the time intervals corresponding to the labeled activities. ### Detailed Analysis or Content Details The chart displays three distinct signal lines (x, y, z) over time. The signals exhibit varying patterns and amplitudes, which change significantly with different activities. **Activity Segments and Signal Characteristics:** 1. **"walk" (approx. 0 to 1500):** * **x (blue):** Relatively low amplitude, oscillating around 0, with some minor fluctuations. * **y (orange):** Moderate amplitude, oscillating with a noticeable pattern, generally between -1 and -0.5. * **z (green):** High amplitude, showing a consistent, rhythmic pattern of peaks and troughs, ranging from approximately -1.5 to 2. 2. **"skip" (approx. 1500 to 2200):** * **x (blue):** Slightly increased amplitude compared to "walk", oscillating around 0. * **y (orange):** High amplitude, with sharp, rapid oscillations, reaching peaks around -0.5 and troughs around -1.5. * **z (green):** Very high amplitude, with a more intense and rapid rhythmic pattern than "walk", reaching peaks around 2 and troughs around -1.5. 3. **"stay" (approx. 2200 to 3000):** * **x (blue):** Low amplitude, oscillating very close to 0. * **y (orange):** Very low amplitude, oscillating very close to 0. * **z (green):** Low amplitude, oscillating very close to 0, with minimal variation. This indicates a period of stillness. 4. **"jog" (approx. 3000 to 4500):** * **x (blue):** Moderate amplitude, oscillating around 0, with a more pronounced pattern than "walk". * **y (orange):** High amplitude, with a rhythmic pattern, generally between -1 and -0.5. * **z (green):** High amplitude, with a strong, rhythmic pattern, similar to "walk" but with slightly higher frequency and amplitude, reaching peaks around 2 and troughs around -1.5. 5. **"walk" (approx. 4500 to 5500):** * **x (blue):** Similar to the first "walk" segment, low to moderate amplitude around 0. * **y (orange):** Similar to the first "walk" segment, moderate amplitude, oscillating between -1 and -0.5. * **z (green):** Similar to the first "walk" segment, high amplitude, rhythmic pattern, ranging from approximately -1.5 to 2. 6. **"stUp" (approx. 5500 to 6200):** * **x (blue):** Shows a brief spike and then settles to a low amplitude around 0. * **y (orange):** Shows a brief period of higher amplitude oscillations before settling to a low amplitude around 0. * **z (green):** Shows a brief period of higher amplitude oscillations before settling to a low amplitude around 0. This segment appears to represent a transition, possibly standing up from a seated position. 7. **"stay" (approx. 6200 to 7000):** * **x (blue):** Low amplitude, oscillating very close to 0. * **y (orange):** Very low amplitude, oscillating very close to 0. * **z (green):** Low amplitude, oscillating very close to 0, indicating stillness. 8. **"stDown" (approx. 7000 to 7700):** * **x (blue):** Shows a brief spike and then settles to a low amplitude around 0. * **y (orange):** Shows a brief period of higher amplitude oscillations before settling to a low amplitude around 0. * **z (green):** Shows a brief period of higher amplitude oscillations before settling to a low amplitude around 0. Similar to "stUp", this likely represents sitting down. 9. **"walk" (approx. 7700 to 8500):** * **x (blue):** Moderate amplitude, oscillating around 0. * **y (orange):** Moderate to high amplitude, with a rhythmic pattern. * **z (green):** High amplitude, with a strong, rhythmic pattern, similar to previous "walk" segments. 10. **"stay" (approx. 8500 to 9200):** * **x (blue):** Low amplitude, oscillating very close to 0. * **y (orange):** Very low amplitude, oscillating very close to 0. * **z (green):** Low amplitude, oscillating very close to 0, indicating stillness. 11. **"skip" (approx. 9200 to 9800):** * **x (blue):** Increased amplitude compared to "walk", oscillating around 0. * **y (orange):** High amplitude, with sharp, rapid oscillations. * **z (green):** Very high amplitude, with an intense and rapid rhythmic pattern, similar to the first "skip" segment. 12. **"jog" (approx. 9800 to 10800):** * **x (blue):** Moderate amplitude, oscillating around 0. * **y (orange):** High amplitude, with a rhythmic pattern. * **z (green):** High amplitude, with a strong, rhythmic pattern, similar to previous "jog" segments. **General Trends:** * The 'z' signal (green) consistently shows the highest amplitude during dynamic activities like walking, skipping, and jogging, suggesting it might be capturing the primary motion axis. * The 'y' signal (orange) also shows significant activity during dynamic movements, particularly during skipping and jogging, and exhibits a distinct pattern during walking. * The 'x' signal (blue) generally has the lowest amplitude during dynamic activities, often oscillating around zero, but shows some variation. * Periods labeled "stay" consistently show very low signal amplitudes across all three axes, indicating minimal movement. * The "stUp" and "stDown" segments show a transition from a low-amplitude "stay" state to a brief period of increased signal activity before returning to a low-amplitude state, which is characteristic of the motion involved in standing up or sitting down. ### Key Observations * The "stay" periods are clearly distinguishable by their near-zero signal values across all axes. * "Skip" and "jog" activities exhibit higher signal amplitudes and more rapid oscillations compared to "walk". * The "stUp" and "stDown" activities show a characteristic transient signal pattern, distinct from continuous movement or stillness. * The repetition of activities (e.g., "walk", "stay", "skip", "jog") allows for comparison of signal patterns under similar conditions. ### Interpretation This chart demonstrates the ability of multi-axis sensor data to differentiate between various human physical activities. The distinct signal patterns observed for each activity (walk, skip, stay, jog, stUp, stDown) suggest that these signals can be used as features for activity recognition systems. * **Signal Dynamics and Activity:** The amplitude and frequency of the signals, particularly the 'z' and 'y' axes, are directly correlated with the intensity and type of physical movement. Higher intensity activities like skipping and jogging produce larger and more rapid signal variations. * **Baseline for Stillness:** The "stay" segments provide a clear baseline, showing minimal sensor noise when the body is at rest. This is crucial for distinguishing between actual movement and sensor drift or background noise. * **Transitional Movements:** The "stUp" and "stDown" segments highlight how sensor data can capture the dynamics of transitions between states (e.g., sitting to standing). The brief bursts of activity indicate the forces and movements involved in these actions. * **Potential for Classification:** The clear visual separation of activity patterns suggests that machine learning models could be trained on this type of data to automatically classify human activities based on sensor readings. The consistency of patterns for repeated activities (e.g., multiple "walk" segments) reinforces this potential. * **Peircean Investigative Reading:** The data can be interpreted as a semiotic representation of human motion. The sensor signals act as signs, where the specific patterns (the interpretant) allow us to infer the object (the activity). The chart presents a series of indices (the signals) that point to the underlying physical actions. The repetition of activities allows for the establishment of a more robust indexical relationship, moving towards a symbolic understanding of the data. The chart effectively demonstrates a form of embodied cognition, where the physical act of movement is translated into a digital signal that can be interpreted. The underlying assumption is that each activity has a unique kinetic signature.

\n ## Time Series Chart: Sensor Signal During Activities ### Overview The image presents a time series chart displaying sensor signal data over time, segmented into different activity types. The chart shows three distinct signal lines (x, y, and z) fluctuating in amplitude as the activity changes. The x-axis represents time, and the y-axis represents the signal strength. The activities are labeled above the chart, indicating the type of movement or state being recorded. ### Components/Axes * **X-axis:** Time (ranging from approximately 0 to 11000) * **Y-axis:** Signal (ranging from approximately -2 to 2) * **Legend:** Located in the top-right corner, identifies the three signal lines: * x (represented by a blue line) * y (represented by an orange line) * z (represented by a green line) * **Activity Labels:** Placed horizontally above the chart, marking time intervals with activity names: walk, skip, stay, jog, walk, stUp, stay, stDown, walk, stay, skip, jog. * **Vertical Lines:** Thin vertical lines are present at the boundaries of each activity segment, visually separating the different activities. ### Detailed Analysis The chart displays three time series, each representing a different sensor axis (x, y, z). The signal values fluctuate over time, with distinct patterns corresponding to each activity. * **x (Blue Line):** The x-axis signal generally exhibits smaller amplitude fluctuations compared to the y and z axes. It shows a relatively stable signal during "stay" periods and more variation during dynamic activities like "walk," "skip," and "jog." * **y (Orange Line):** The y-axis signal shows significant fluctuations, particularly during "skip," "stUp," and "stDown" activities. It appears to have a more pronounced positive and negative swing during these movements. * **z (Green Line):** The z-axis signal exhibits the largest amplitude fluctuations and is the most visually dominant signal in the chart. It shows clear patterns related to the different activities. For example, during "walk" and "jog," the signal oscillates with a relatively consistent frequency. Here's a breakdown of signal characteristics for each activity (approximate values): * **walk (0-1000, 4000-5000, 8000-9000):** z fluctuates between -1.5 and 1.5, y between -0.5 and 0.5, x is relatively stable around 0. * **skip (1000-2000, 10000-11000):** z fluctuates between -2 and 2, y between -1 and 1, x shows some variation but remains smaller in amplitude. * **stay (2000-3000, 6000-7000, 9000-10000):** z is relatively stable around 0, y is also close to 0, x is minimal. * **jog (3000-4000, 11000-end):** z fluctuates between -1.5 and 1.5, y between -0.5 and 0.5, x is relatively stable around 0. * **stUp (5000-6000):** y shows a large positive spike, z fluctuates between -1 and 1, x is minimal. * **stDown (7000-8000):** y shows a large negative spike, z fluctuates between -1 and 1, x is minimal. ### Key Observations * The "stay" activity consistently exhibits the lowest signal amplitude across all three axes, indicating minimal movement. * "Skip," "stUp," and "stDown" activities generate the highest signal amplitude, particularly in the y-axis, suggesting significant and rapid changes in orientation. * The z-axis signal appears to be the most sensitive to changes in activity, showing the most pronounced fluctuations. * The x-axis signal is the least sensitive, providing a relatively stable baseline. ### Interpretation This chart likely represents data from an accelerometer or similar sensor measuring movement along three axes. The different signal patterns correspond to different human activities. The data suggests that the sensor can effectively differentiate between static ("stay") and dynamic ("walk," "skip," "jog") activities. The "stUp" and "stDown" activities likely represent standing up and sitting down, respectively, and are characterized by a strong signal change in the y-axis, indicating vertical movement. The consistent patterns observed for each activity suggest that this data could be used to develop an activity recognition system. The sensor data could be used as input to a machine learning model trained to classify different activities based on the signal characteristics. The outliers, such as the large spikes during "stUp" and "stDown," could be used as key features for accurate classification. The relative stability of the x-axis could be used to filter out noise or compensate for sensor drift.

\n ## Time-Series Chart: Multi-Signal Activity Segmentation ### Overview The image displays a time-series plot containing three continuous signals (x, y, z) recorded over a period of approximately 10,500 time units. The data is segmented into distinct temporal regions, each labeled with a specific physical activity. Vertical lines of different colors demarcate the boundaries between these activity segments. ### Components/Axes * **Chart Type:** Multi-line time-series plot with activity segmentation. * **X-Axis:** Labeled "Time". The scale runs from 0 to just beyond 10,000, with major tick marks at 0, 2000, 4000, 6000, 8000, and 10000. * **Y-Axis:** Labeled "Signal". The scale runs from -2 to 2, with major tick marks at -2, -1, 0, 1, and 2. * **Legend:** Located in the top-right corner of the plot area. It defines three data series: * `x` (blue line) * `y` (orange line) * `z` (green line) * **Activity Segments & Boundaries:** The plot is divided by vertical lines. The color of the line appears to correspond to the activity type. The segments, from left to right, are: 1. **walk** (Start ~0, End ~1200). Bounded by a red vertical line on the right. 2. **skip** (Start ~1200, End ~2000). Bounded by a blue vertical line on the right. 3. **stay** (Start ~2000, End ~2800). Bounded by a red vertical line on the right. 4. **jog** (Start ~2800, End ~3800). Bounded by a blue vertical line on the right. 5. **walk** (Start ~3800, End ~4800). Bounded by a purple vertical line on the right. 6. **stUp** (Start ~4800, End ~5600). Bounded by a purple vertical line on the right. 7. **stay** (Start ~5600, End ~6400). Bounded by a red vertical line on the right. 8. **stDown** (Start ~6400, End ~7200). Bounded by a blue vertical line on the right. 9. **walk** (Start ~7200, End ~8000). Bounded by a purple vertical line on the right. 10. **stay** (Start ~8000, End ~8800). Bounded by a red vertical line on the right. 11. **skip** (Start ~8800, End ~9600). Bounded by a blue vertical line on the right. 12. **jog** (Start ~9600, End ~10500+). ### Detailed Analysis **Signal Behavior by Activity Segment:** 1. **walk (0-1200):** * **z (green):** High-amplitude, regular oscillations between approx. -1.5 and +1.5. * **y (orange):** Consistently negative, oscillating between approx. -1.0 and -2.0. * **x (blue):** Low-amplitude noise centered around 0. 2. **skip (1200-2000):** * **z (green):** Very high-amplitude, dense oscillations, frequently exceeding the plot limits (clipping at ±2). * **y (orange):** Similar to the first walk segment, negative and oscillating. * **x (blue):** Low-amplitude noise around 0. 3. **stay (2000-2800):** * **All signals (x, y, z):** Flat lines with minimal noise. `z` and `x` are near 0. `y` is stable at approximately -1.1. 4. **jog (2800-3800):** * **z (green):** Extremely high-frequency, high-amplitude oscillations, consistently clipping at the plot limits (±2). * **y (orange):** High-amplitude oscillations, ranging from approx. -2.0 to 0. * **x (blue):** Shows more activity than in walk/skip, with oscillations between approx. -0.5 and +0.5. 5. **walk (3800-4800):** * Similar pattern to the first walk segment. `z` oscillates strongly, `y` is negative, `x` is low-noise. 6. **stUp (4800-5600):** * **z (green):** Moderate oscillations, amplitude lower than walking. * **y (orange):** Shows a distinct pattern: a sharp negative spike at the start, followed by oscillations between approx. -1.5 and -0.5. * **x (blue):** Low-amplitude oscillations. 7. **stay (5600-6400):** * Flat lines, nearly identical to the first "stay" segment. `y` holds at ~-1.1. 8. **stDown (6400-7200):** * **z (green):** Moderate oscillations. * **y (orange):** Distinct pattern with a positive spike at the start, followed by oscillations between approx. -1.5 and 0. * **x (blue):** Low-amplitude oscillations. 9. **walk (7200-8000):** * Consistent with previous walk segments. 10. **stay (8000-8800):** * Flat lines, consistent with previous stay segments. 11. **skip (8800-9600):** * Consistent with the first skip segment: very high-amplitude `z` and `y` signals. 12. **jog (9600-10500+):** * Consistent with the first jog segment: maximum amplitude, high-frequency oscillations in `z` and `y`. ### Key Observations * **Clear Signal Differentiation:** Each activity produces a distinct signature across the three signal axes. "Stay" is characterized by flat lines. "Walk," "skip," and "jog" show progressively higher amplitude and frequency in the `z` (green) signal. * **Consistent `y` (orange) Offset:** During all dynamic activities (walk, skip, jog, stUp, stDown), the `y` signal is predominantly negative. During static "stay" periods, it holds a stable negative value (~-1.1). * **Segment Boundary Precision:** The transitions between activities are abrupt, as indicated by the immediate change in signal patterns at the vertical boundary lines. * **Signal Clipping:** The `z` signal during "skip" and "jog" activities frequently exceeds the plotted range of -2 to 2, indicating the sensor's output may have saturated. ### Interpretation This chart almost certainly represents **tri-axial accelerometer data** (where x, y, z correspond to physical axes) collected during a sequence of human activities. The data is likely from a wearable sensor (e.g., on the waist or wrist). * **What the data demonstrates:** The distinct signal patterns serve as a "fingerprint" for each activity. This is the foundational data used to train machine learning models for **Human Activity Recognition (HAR)**. The clear segmentation suggests this is either labeled training data or the output of a perfect activity classifier. * **Relationship between elements:** The vertical lines and labels provide the "ground truth" annotation for the raw sensor signals. The `y` axis's consistent negative bias during movement might indicate the sensor's orientation relative to gravity. The `z` axis appears to be the primary axis of motion for these activities. * **Notable patterns/anomalies:** * The "stUp" (stand up) and "stDown" (sit/lie down) segments show unique transient spikes in the `y` signal, capturing the specific motion of changing posture. * The near-perfect flatness during "stay" segments indicates the subject was completely still, which is ideal for calibration. * The clipping during "jog" and "skip" is a practical data quality issue; in a real-world application, this would necessitate adjusting the sensor's measurement range.

# Technical Document Extraction: Signal Analysis Chart ## 1. Axis Labels and Markers - **X-Axis (Horizontal):** - Label: `Time` - Markers: `0`, `2000`, `4000`, `6000`, `8000`, `10000` - **Y-Axis (Vertical):** - Label: `Signal` - Markers: `-2`, `-1`, `0`, `1`, `2` ## 2. Legend - **Position:** Top-right corner - **Labels and Colors:** - `x` (blue) - `y` (orange) - `z` (green) ## 3. Activity Segments and Labels Vertical lines segment the chart into labeled activity intervals. Each segment includes: - **Start/End Time** (approximate): - `walk`: 0–1000 - `skip`: 1000–2000 - `stay`: 2000–3000 - `jog`: 3000–4000 - `walk`: 4000–5000 - `stUp`: 5000–6000 - `stay`: 6000–7000 - `stDown`: 7000–8000 - `walk`: 8000–9000 - `stay`: 9000–10000 - `skip`: 10000–11000 - `jog`: 11000–12000 ## 4. Data Series Trends ### X-Series (Blue) - **Trend:** - High amplitude fluctuations during `walk`, `jog`, and `skip`. - Near-zero baseline during `stay` and `stUp`. - **Key Data Points:** - Peaks at ±1.5–2.0 during active phases. - Minima at ±0.1 during stationary phases. ### Y-Series (Orange) - **Trend:** - Moderate amplitude during `walk` and `jog`. - Near-zero baseline during `stay` and `stUp`. - **Key Data Points:** - Peaks at ±1.0–1.2 during active phases. - Minima at ±0.05 during stationary phases. ### Z-Series (Green) - **Trend:** - High amplitude during `walk`, `jog`, and `skip`. - Near-zero baseline during `stay` and `stUp`. - **Key Data Points:** - Peaks at ±1.8–2.0 during active phases. - Minima at ±0.1 during stationary phases. ## 5. Cross-Referenced Legend Validation - **Color Consistency:** - Blue (`x`) matches all blue lines. - Orange (`y`) matches all orange lines. - Green (`z`) matches all green lines. ## 6. Spatial Grounding - **Legend Position:** Top-right corner (no explicit coordinates provided). - **Axis Alignment:** - X-axis spans 0–12,000 (time). - Y-axis spans -2 to 2 (signal). ## 7. Activity-Specific Observations - **Walk:** - X and Z series exhibit synchronized high-amplitude oscillations. - Y series shows lower but consistent activity. - **Jog:** - X and Z series peak at similar magnitudes (~2.0). - Y series lags slightly behind X/Z. - **Stay:** - All series flatten to near-zero baseline. - **StUp/StDown:** - Minimal signal variation across all axes. ## 8. Data Table Reconstruction | Activity | Start Time | End Time | X-Series Peak | Y-Series Peak | Z-Series Peak | |------------|------------|----------|---------------|---------------|---------------| | walk | 0 | 1000 | ±1.5–2.0 | ±1.0–1.2 | ±1.8–2.0 | | skip | 1000 | 2000 | ±1.2–1.5 | ±0.8–1.0 | ±1.5–1.8 | | stay | 2000 | 3000 | ±0.1 | ±0.05 | ±0.1 | | jog | 3000 | 4000 | ±1.8–2.0 | ±1.2–1.4 | ±1.9–2.0 | | walk | 4000 | 5000 | ±1.5–2.0 | ±1.0–1.2 | ±1.8–2.0 | | stUp | 5000 | 6000 | ±0.1 | ±0.05 | ±0.1 | | stay | 6000 | 7000 | ±0.1 | ±0.05 | ±0.1 | | stDown | 7000 | 8000 | ±0.1 | ±0.05 | ±0.1 | | walk | 8000 | 9000 | ±1.5–2.0 | ±1.0–1.2 | ±1.8–2.0 | | stay | 9000 | 10000 | ±0.1 | ±0.05 | ±0.1 | | skip | 10000 | 11000 | ±1.2–1.5 | ±0.8–1.0 | ±1.5–1.8 | | jog | 11000 | 12000 | ±1.8–2.0 | ±1.2–1.4 | ±1.9–2.0 | ## 9. Additional Notes - **Language:** All text is in English. - **Missing Elements:** No explicit chart title or numerical data table in the image. - **Assumptions:** Time intervals for activities are approximate based on visual segmentation.