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Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →To estimate how long a motion-powered wearable sensor will run, calculate the energy available from the harvester over the user’s actual activity pattern, calculate the sensor’s average energy demand, account for conversion and leakage losses, and then compare the two over the storage voltage window. For a capacitor store, the usable energy is Eusable = ½ C (Vhigh2 − Vlow2). Storage-only runtime is approximately t = Eusable × ηsystem / Pload. If motion continues while the sensor operates, use the net balance Pnet = Pharvested,avg − Pload,avg and check whether the stored energy can cover periods of rest.
A harvester’s peak rating is not a runtime estimate. Human motion is intermittent, changes frequency and amplitude, and may stop for hours. A design can be energy-neutral on a daily average yet brown out whenever the wearer sits still unless its storage and power-management circuit bridge that gap.
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What “runtime” means in a harvested-energy wearable
Battery-powered devices usually quote runtime from a nearly fixed capacity and a measured average current. A kinetic wearable has a different problem: energy arrives in irregular packets, while the sensor may need a continuous supply. Runtime therefore has two parts:
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- Energy-neutral operation: whether average harvested power over the wearer’s activity profile at least matches average consumption.
These are not interchangeable. Positive average net power means storage tends to charge over the chosen activity period; it does not prove that the voltage will never fall below the converter’s shutdown threshold during a quiet interval. Conversely, a negative average net power can still support a short measurement session if the store starts full.
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Kamran Sayrafian, Dora Budic and Dina Simunic state the NIST/IEEE CogInfoCom objective as “our objective is to estimate the average amount of kinetic energy that can be harvested to power a wearable device.” That wording is important: the quantity to estimate is an average over representative movement, not a best-case pulse from a test bench.
Step 1: Build a realistic harvested-power profile
Measure the body motion where the device will be worn
Start with the intended body location—wrist, ankle, knee, torso or another attachment point. Acceleration at one location cannot be substituted casually for acceleration at another. Record representative sessions that include the activities the wearer actually performs, plus low-motion and sedentary periods. A useful profile might contain walking at normal and slow speeds, stairs, commuting, desk work, standing, and sleep, with the duration of each segment preserved.
The NIST method estimates average kinetic energy by measuring body acceleration at likely wearable locations and applying a micro-harvester model. In practice, synchronize the acceleration record with the harvester’s electrical output, then calculate the average electrical power for each activity segment. Keep the frequency, amplitude and direction of motion because a harvester that responds well to one movement may produce little from another.
Do not use a peak specification as a daily yield
Peak power normally comes from a defined laboratory motion, load and frequency. It says how much power the structure produced under that condition, not how much a person will provide while walking, sitting and sleeping. The 11.24 mW maximum reported at 3 Hz by Wiley Energy Technology in 2026 is a measured maximum for a specific piezoelectric–triboelectric structure under a defined low-frequency test. It is not a general wearable guarantee.
For the same reason, the 7.5248 µW reported during slow walking by the WearETE textile triboelectric system in Scientific Reports (2017) is a system-specific example. It should be used as an order-of-magnitude reference for that tested construction, not as a universal walking output. A Sensors paper from 2016 reported 6–74 µW from piezoelectric transducers mounted at different body joints across walking, stairs, jogging and running in its own setup; the range illustrates how strongly placement and activity affect the result.
Average over irregular motion
Human movement is non-stationary. A short burst can charge a capacitor quickly, followed by a long interval in which leakage and sensor consumption lower the voltage. Compute an average for each activity and then combine them using the time spent in each activity:
Pharvested,avg = (Σ Pi × Δti) / Σ Δti
Use the same interval for the load profile. If the device is expected to work during a particular commute or shift, calculate that schedule rather than an abstract 24-hour average. Include the minimum expected motion case; designing only for an active user can hide brownouts in real use.
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Step 2: Calculate the sensor’s average load
Break the duty cycle into operating states
Use measured current and voltage for every state instead of quoting the active-mode rating. At minimum, separate:
- deep sleep or standby current;
- sensor warm-up and sampling;
- local processing or feature extraction;
- radio connection, packet transmission and receive windows;
- regulator quiescent current;
- indicator, memory or security operations; and
- startup and shutdown transients.
For each state, record power and duration. The average load is the time-weighted sum:
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Pload,avg = Σ(Pstate × tstate) / T
A sensor that samples continuously but transmits one short packet every few minutes may consume far less on average than its radio’s active-mode number suggests. The radio burst can still determine the required capacitor because its instantaneous current may pull the supply below the converter’s minimum input voltage.
Include conversion-side consumption
Measure the regulator or energy-management integrated circuit in the states the wearable actually uses. Quiescent current flows while the sensor sleeps, and leakage through the harvester, rectifier, capacitor and protection components can be comparable to a micro-watt load. Include these currents in the load budget or represent them in the system-efficiency term used later; do not count them twice.
Step 3: Calculate usable capacitor energy
Use the converter’s real voltage window
For a capacitor of capacitance C, the energy between two voltage thresholds is:
Eusable = ½ C (Vhigh2 − Vlow2)
Vhigh is the highest voltage at which charging stops or regulation changes state. Vlow is the lowest voltage at which the load and converter still operate. Do not use the capacitor’s rated voltage as Vhigh unless the complete circuit can actually charge to that voltage and the load can use the energy down to the stated lower limit.
The squared voltages make the window matter more than a simple voltage difference suggests. Raising the upper threshold can add substantial energy; raising the lower cutoff removes energy from the usable range. Real capacitance also varies with bias, temperature and tolerance, so use the value measured or guaranteed under the operating conditions when the design is close to its margin.
Check the pulse requirement separately
The energy equation gives total joules, not the capacitor’s ability to deliver a radio burst. Verify the capacitor’s equivalent series resistance, the converter’s peak-current limit and the voltage droop during the burst. If the converter disconnects at a higher instantaneous voltage than its nominal low threshold, use that higher value in the energy calculation.
Step 4: Apply system losses and estimate storage runtime
Rectification, voltage conversion, wiring resistance, leakage and control circuitry all reduce the energy delivered to the sensor. Represent their combined effect with ηsystem:
truntime ≈ Eusable × ηsystem / Pload,avg
Use an efficiency measured over the relevant input-power and voltage range. Converter efficiency at a high harvested input may not apply when the harvester is producing only a few microwatts. Likewise, a rectifier’s forward loss can consume a large fraction of a low-voltage pulse. If you have separate measurements, calculate the product of rectifier, converter and wiring efficiencies and subtract leakage energy explicitly.
Use the net-power equation when motion and load overlap
When the harvester is active during operation, compare average powers:
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Pnet = Pharvested,avg − Pload,avg
- If
Pnet > 0, the store charges on average during that profile. - If
Pnet = 0, the system is energy-neutral on average but still vulnerable to voltage ripple, leakage and motion-free intervals. - If
Pnet < 0, the store discharges and runtime depends on its starting energy.
Apply efficiency consistently. A practical approach is to convert harvested input to usable load-side power first, then subtract the measured load. This avoids treating raw mechanical or rectifier-side power as if it were available to the sensor.
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After calculating a result, instrument the finished hardware. Log capacitor voltage, harvester current or power, sensor state and radio activity while the device follows its real duty cycle. A voltage-versus-time trace reveals threshold crossings, burst-induced droop and leakage that a single average number hides.
WearETE describes the capacitor method this way: “A capacitor is used to estimate the generated power, which can be calculated by Equation (5).” Its relationship is:
Pout(t) = C × V(t) × dV(t)/dt
Estimate the derivative from a filtered voltage trace and average the result over an interval. WearETE recommends interval averaging because human motion is irregular. Use intervals long enough to contain several movement cycles, but short enough to distinguish walking from rest. During a known load state, subtract the load-side consumption if you are trying to isolate harvester output rather than net storage change.
Repeat the test with a fully charged store, a partially charged store and the minimum-motion profile. Record the voltage at which the converter starts, stops, throttles or resets. Those measured thresholds replace nominal values in the runtime calculation.
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Worked calculation: a 220 µF storage capacitor
Assume a 220 µF capacitor, Vhigh = 3.3 V, Vlow = 2.2 V, an average sensor load of 100 µW and an overall usable efficiency of 70%:
- Calculate the capacitor’s usable energy:
½ × 220 × 10−6 × (3.32 − 2.22) ≈ 0.000665 J. - Apply the assumed system efficiency:
0.000665 J × 0.70 ≈ 0.000466 Jdelivered to the load. - Divide by the 100 µW average load:
0.000466 J / 0.0001 W ≈ 4.7 s.
This is a storage-only calculation template, not a measured runtime. It assumes the capacitor begins at 3.3 V, the load can operate to 2.2 V, the 70% efficiency applies throughout the discharge, and the average load really is 100 µW. Replace every assumed value with measurements from the target sensor. If harvesting continues while the sensor runs, add the usable harvested power to the balance; if the wearer stops moving, the result reverts toward the storage-only case.
What published output figures can—and cannot—tell you
| Reported figure | Test context | How to use it |
|---|---|---|
| 11.24 mW maximum at 3 Hz | Measured in a 2026 Wiley Energy Technology study for a specific piezoelectric–triboelectric structure under a defined low-frequency test | Use as a device-specific peak reference, not a guaranteed wearable average |
| 7.5248 µW during slow walking | Reported by WearETE in Scientific Reports (2017) for its tested textile triboelectric system | Use as a system-specific slow-walking example |
| 6–74 µW across locomotion activities | 2016 Sensors report using piezoelectric transducers at different body joints during walking, stairs, jogging and running | Use to illustrate variation with activity and placement |
| 220 µF capacitor and 2-second minimum uninterrupted execution per charging cycle | KineticWear battery-free activity-recognition prototype reported in ACM Transactions on Internet of Things (2025) | Use as an implementation-specific storage and workload example |
| 24.94% average power efficiency | WearETE’s calibrated textile harvester under its tested conditions in Scientific Reports (2017) | Use only when the new design has comparable operating conditions |
The KineticWear result is particularly useful for sizing a prototype because it couples a 220 µF store with a stated minimum uninterrupted execution time of 2 seconds per charging cycle. It does not establish that every 220 µF capacitor will run every wearable for 2 seconds; the workload, converter thresholds and implementation determine the result.
Design for sedentary intervals and brownout recovery
Determine the longest interval in which the user may provide little or no motion. The store must supply sleep current, sensor sampling and any scheduled radio burst for that interval. Calculate the required energy as:
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Egap = Pload,avg during gap × tgap / ηdelivery
Then choose Vhigh, Vlow and capacitance so that the usable energy exceeds Egap with margin. Add margin for capacitor tolerance, temperature, aging and leakage. If the capacitor cannot bridge the gap, options include lowering the sampling rate, buffering radio data, shortening transmissions, increasing storage, reducing converter quiescent current or adding a rechargeable secondary store.
Firmware should treat low energy as a normal state. Use the converter’s power-good or undervoltage signal to defer a radio burst, save state, and resume after the capacitor recovers. A clean restart path prevents repeated brownout loops in which the sensor wakes, transmits, collapses the voltage and resets before completing its task.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to compare candidate kinetic-harvester designs
Compare designs with the same motion schedule and the same sensor duty cycle. The most useful criteria are:
- Average net electrical power: output after rectification and conversion over the real activity profile, not the mechanical or open-circuit peak.
- Usable storage energy: capacitance or cell capacity within the converter’s actual voltage window.
- Power-management efficiency: rectifier loss, converter efficiency at low input power, quiescent current and leakage.
- Motion sensitivity: frequency and amplitude range, directional response and dependence on body placement.
- Wearability: size, mass, comfort, attachment method and mechanical durability.
- Rest behavior: voltage decay and the time the system can remain functional without new motion.
A harvester with a lower peak but better low-frequency response and lower leakage can outperform a higher-peak design over a full day. Storage and energy-management circuitry deserve equal attention because harvested energy may arrive while the sensor is asleep and must be buffered for a later processing or radio burst.
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Common estimation mistakes and fixes
Using active current as average current
Symptom: the predicted runtime is far shorter than measured operation, or the design appears impossible on paper.
Fix: integrate current over the complete sleep, sample, process and transmit schedule. Keep radio burst power for pulse sizing, but use its time-weighted contribution for average energy.
Using the capacitor’s full rated voltage
Symptom: the calculation predicts more joules than the converter can deliver.
Fix: use the measured charge-stop and load-cutoff thresholds in the squared-voltage equation.
Ignoring quiescent and leakage currents
Symptom: the capacitor discharges during an apparently idle test.
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Fix: measure the complete power path with the sensor asleep, including regulator, rectifier, protection and measurement circuitry.
Quoting harvester peak power as continuous power
Symptom: the prototype works during a shake or jog but resets during ordinary walking or sitting.
Fix: characterize output by activity and average it using the expected time fractions. Include the minimum-motion case.
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Symptom: the daily energy balance is positive, yet the sensor brownouts during radio transmissions or desk work.
Fix: inspect the voltage trace at burst times and across the longest rest interval. Increase storage, reduce burst energy or schedule transmissions when the store is sufficiently charged.
Assuming a published efficiency transfers directly
Symptom: a literature efficiency produces an optimistic runtime.
Fix: treat published efficiency as conditional on its harvester, frequency, load and calibration. Measure the complete target system at the low input powers it will actually see.
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End-to-end calculation checklist
- Define the body location, user activities and longest expected motion-free interval.
- Measure acceleration and harvester output for each activity, including slow movement and rest.
- Convert those records into average usable electrical power after rectification and conversion.
- Measure every sensor operating state and calculate the time-weighted average load.
- Record converter start, stop and regulation thresholds.
- Calculate capacitor energy with
½ C (Vhigh2 − Vlow2), using the real voltage window. - Apply measured system efficiency and estimate storage-only runtime.
- Calculate net power for each activity and for the complete schedule.
- Check that storage covers the longest sedentary gap and the largest radio or processing burst.
- Validate with a voltage-versus-time trace while the finished sensor performs its actual duty cycle.
Decision rule for a motion-powered wearable
Call the design viable only when both conditions hold: its average usable harvested power meets the intended duty-cycle load over the target activity profile, and its storage window covers the longest expected low-motion interval with enough voltage margin for peak bursts. If either condition fails, changing the headline harvester rating alone will not solve the problem; adjust the duty cycle, storage, converter losses, placement or mechanical design and repeat the measurement.
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